Modelling domestic stock energy use and heat-related health risk : a GIS-based bottom-up modelling approach

Energy Technology Data Exchange (ETDEWEB)

Mavrogianni, A.; Davies, M. [Univ. College London, London (United Kingdom). Bartlett School of Graduate Studies; Chalabi, Z.; Wilkinson, P. [London School of Hygiene and Tropical Medecine, London (United Kingdom); Kolokotroni, M. [Brunel Univ., London (United Kingdom). School of Engineering Design

2009-07-01

Approximately 8 per cent of the carbon dioxide (CO{sub 2}) emissions produced in the United Kingdom are produced in London, one of the fastest growing cities worldwide. Based on the projected rates of population and economic growth, a 15 per cent increase of emissions is predicted. In addition to the national target to cut emissions by 80 per cent by 2050, the Mayor of London Climate Change Action Plan set a target to reduce London's CO{sub 2} emissions by 60 per cent by 2025. Significant carbon savings can be achieved in the building sector, particularly since 38 per cent of the total delivered energy in London is associated with domestic energy use. This paper demonstrated a systematic approach towards exploring the impact of urban built form and the combined effect of climate change and the urban heat island (UHI) phenomenon on the levels of domestic energy consumption and heat-related health risk in London. It presented work in progress on the development of a GIS-based energy consumption model and heat vulnerability index of the Greater London Area domestic stock. Comparison of the model output for 10 case study areas with topdown energy statistics revealed that the model successfully ranks areas based on their domestic space heating demand. The health module can be used to determine environments prone to higher risk of heat stress by investigating urban texture factors. A newly developed epidemiological model will be feed into the health module to examine the influence on risk of heat-related mortality of local urban built form characteristics. The epidemiological model is based on multi-variable analysis of deaths during heat wave and non-heat wave days. 29 refs., 1 tab., 7 figs.

A comparison of models for risk assessment

International Nuclear Information System (INIS)

Kellerer, A.M.; Jing Chen

1993-01-01

Various mathematical models have been used to represent the dependence of excess cancer risk on dose, age and time since exposure. For solid cancers, i.e. all cancers except leukaemia, the so-called relative risk model is usually employed. However, there can be quite different relative risk models. The most usual model for the quantification of excess tumour rate among the atomic bomb survivors has been a dependence of the relative risk on age at exposure, but it has been shown recently that an age attained model can be equally applied, to represent the observations among the atomic bomb survivors. The differences between the models and their implications are explained. It is also shown that the age attained model is similar to the approaches that have been used in the analysis of lung cancer incidence among radon exposed miners. A more unified approach to modelling of radiation risks can thus be achieved. (3 figs.)

Retrospective look at Rn-induced lung cancer mortality from the viewpoint of a relative risk model

International Nuclear Information System (INIS)

Puskin, J.S.; Yang, Y.

1988-01-01

The potential contribution to U.S. lung cancer deaths from 1930 to 1987 from indoor 222 Rn exposures is investigated from the standpoint of a constant relative risk model. Based on this model, which assumes a Rn risk proportional to the baseline lung cancer risk from other causes, the rate of Rn-induced lung cancer mortality has been increasing sharply since 1930. However, the estimated proportion of lung cancer deaths attributable to Rn has remained fairly constant. Applying the range of coefficients the U.S. Environmental Protection Agency employs in assessing the risk from indoor Rn, it is estimated that 8-25% of all current lung cancer deaths are attributable to past Rn exposures. The major sources of uncertainty in the estimates are discussed

A risk-based microbiological criterion that uses the relative risk as the critical limit

DEFF Research Database (Denmark)

Andersen, Jens Kirk; Nørrung, Birgit; da Costa Alves Machado, Simone

2015-01-01

A risk-based microbiological criterion is described, that is based on the relative risk associated to the analytical result of a number of samples taken from a food lot. The acceptable limit is a specific level of risk and not a specific number of microorganisms, as in other microbiological...... criteria. The approach requires the availability of a quantitative microbiological risk assessment model to get risk estimates for food products from sampled food lots. By relating these food lot risk estimates to the mean risk estimate associated to a representative baseline data set, a relative risk...... estimate can be obtained. This relative risk estimate then can be compared with a critical value, defined by the criterion. This microbiological criterion based on a relative risk limit is particularly useful when quantitative enumeration data are available and when the prevalence of the microorganism...

Using prior risk-related knowledge to support risk management decisions: lessons learnt from a tunneling project.

Science.gov (United States)

Cárdenas, Ibsen Chivatá; Al-Jibouri, Saad S H; Halman, Johannes I M; van de Linde, Wim; Kaalberg, Frank

2014-10-01

The authors of this article have developed six probabilistic causal models for critical risks in tunnel works. The details of the models' development and evaluation were reported in two earlier publications of this journal. Accordingly, as a remaining step, this article is focused on the investigation into the use of these models in a real case study project. The use of the models is challenging given the need to provide information on risks that usually are both project and context dependent. The latter is of particular concern in underground construction projects. Tunnel risks are the consequences of interactions between site- and project-specific factors. Large variations and uncertainties in ground conditions as well as project singularities give rise to particular risk factors with very specific impacts. These circumstances mean that existing risk information, gathered from previous projects, is extremely difficult to use in other projects. This article considers these issues and addresses the extent to which prior risk-related knowledge, in the form of causal models, as the models developed for the investigation, can be used to provide useful risk information for the case study project. The identification and characterization of the causes and conditions that lead to failures and their interactions as well as their associated probabilistic information is assumed to be risk-related knowledge in this article. It is shown that, irrespective of existing constraints on using information and knowledge from past experiences, construction risk-related knowledge can be transferred and used from project to project in the form of comprehensive models based on probabilistic-causal relationships. The article also shows that the developed models provide guidance as to the use of specific remedial measures by means of the identification of critical risk factors, and therefore they support risk management decisions. Similarly, a number of limitations of the models are

Multi-hazard risk analysis related to hurricanes

Science.gov (United States)

Lin, Ning

Hurricanes present major hazards to the United States. Associated with extreme winds, heavy rainfall, and storm surge, landfalling hurricanes often cause enormous structural damage to coastal regions. Hurricane damage risk assessment provides the basis for loss mitigation and related policy-making. Current hurricane risk models, however, often oversimplify the complex processes of hurricane damage. This dissertation aims to improve existing hurricane risk assessment methodology by coherently modeling the spatial-temporal processes of storm landfall, hazards, and damage. Numerical modeling technologies are used to investigate the multiplicity of hazards associated with landfalling hurricanes. The application and effectiveness of current weather forecasting technologies to predict hurricane hazards is investigated. In particular, the Weather Research and Forecasting model (WRF), with Geophysical Fluid Dynamics Laboratory (GFDL)'s hurricane initialization scheme, is applied to the simulation of the wind and rainfall environment during hurricane landfall. The WRF model is further coupled with the Advanced Circulation (AD-CIRC) model to simulate storm surge in coastal regions. A case study examines the multiple hazards associated with Hurricane Isabel (2003). Also, a risk assessment methodology is developed to estimate the probability distribution of hurricane storm surge heights along the coast, particularly for data-scarce regions, such as New York City. This methodology makes use of relatively simple models, specifically a statistical/deterministic hurricane model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, to simulate large numbers of synthetic surge events, and conducts statistical analysis. The estimation of hurricane landfall probability and hazards are combined with structural vulnerability models to estimate hurricane damage risk. Wind-induced damage mechanisms are extensively studied. An innovative windborne debris risk model is

Decreasing Relative Risk Premium

DEFF Research Database (Denmark)

Hansen, Frank

relative risk premium in the small implies decreasing relative risk premium in the large, and decreasing relative risk premium everywhere implies risk aversion. We finally show that preferences with decreasing relative risk premium may be equivalently expressed in terms of certain preferences on risky......We consider the risk premium demanded by a decision maker with wealth x in order to be indifferent between obtaining a new level of wealth y1 with certainty, or to participate in a lottery which either results in unchanged present wealth or a level of wealth y2 > y1. We define the relative risk...... premium as the quotient between the risk premium and the increase in wealth y1–x which the decision maker puts on the line by choosing the lottery in place of receiving y1 with certainty. We study preferences such that the relative risk premium is a decreasing function of present wealth, and we determine...

Neural mechanisms regulating different forms of risk-related decision-making: Insights from animal models.

Science.gov (United States)

Orsini, Caitlin A; Moorman, David E; Young, Jared W; Setlow, Barry; Floresco, Stan B

2015-11-01

Over the past 20 years there has been a growing interest in the neural underpinnings of cost/benefit decision-making. Recent studies with animal models have made considerable advances in our understanding of how different prefrontal, striatal, limbic and monoaminergic circuits interact to promote efficient risk/reward decision-making, and how dysfunction in these circuits underlies aberrant decision-making observed in numerous psychiatric disorders. This review will highlight recent findings from studies exploring these questions using a variety of behavioral assays, as well as molecular, pharmacological, neurophysiological, and translational approaches. We begin with a discussion of how neural systems related to decision subcomponents may interact to generate more complex decisions involving risk and uncertainty. This is followed by an overview of interactions between prefrontal-amygdala-dopamine and habenular circuits in regulating choice between certain and uncertain rewards and how different modes of dopamine transmission may contribute to these processes. These data will be compared with results from other studies investigating the contribution of some of these systems to guiding decision-making related to rewards vs. punishment. Lastly, we provide a brief summary of impairments in risk-related decision-making associated with psychiatric disorders, highlighting recent translational studies in laboratory animals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Validation of visualized transgenic zebrafish as a high throughput model to assay bradycardia related cardio toxicity risk candidates.

Science.gov (United States)

Wen, Dingsheng; Liu, Aiming; Chen, Feng; Yang, Julin; Dai, Renke

2012-10-01

Drug-induced QT prolongation usually leads to torsade de pointes (TdP), thus for drugs in the early phase of development this risk should be evaluated. In the present study, we demonstrated a visualized transgenic zebrafish as an in vivo high-throughput model to assay the risk of drug-induced QT prolongation. Zebrafish larvae 48 h post-fertilization expressing green fluorescent protein in myocardium were incubated with compounds reported to induce QT prolongation or block the human ether-a-go-go-related gene (hERG) K⁺ current. The compounds sotalol, indapaminde, erythromycin, ofoxacin, levofloxacin, sparfloxacin and roxithromycin were additionally administrated by microinjection into the larvae yolk sac. The ventricle heart rate was recorded using the automatic monitoring system after incubation or microinjection. As a result, 14 out of 16 compounds inducing dog QT prolongation caused bradycardia in zebrafish. A similar result was observed with 21 out of 26 compounds which block hERG current. Among the 30 compounds which induced human QT prolongation, 25 caused bradycardia in this model. Thus, the risk of compounds causing bradycardia in this transgenic zebrafish correlated with that causing QT prolongation and hERG K⁺ current blockage in established models. The tendency that high logP values lead to high risk of QT prolongation in this model was indicated, and non-sensitivity of this model to antibacterial agents was revealed. These data suggest application of this transgenic zebrafish as a high-throughput model to screen QT prolongation-related cardio toxicity of the drug candidates. Copyright © 2012 John Wiley & Sons, Ltd.

Relative risk models of lung cancer in uranium miners

Energy Technology Data Exchange (ETDEWEB)

Tomasek, L [National Radiation Protection Institute, Prague (Czech Republic); Placek, V [Inst. for Expertises and Emergencies, Pribram-Kamenna (Czech Republic)

1996-12-31

The study population of the S cohort (studies of underground miners of uranium and other substances as the source of information on long term effects of exposure to radon and its progeny) involve uranium miners, that started underground work at the Jachymov and Horni Slavkov mines in the period 1978-1959, and had worked at least for four years. A total 4320 men satisfied these criteria. During the decade up to 1990, follow-up of the cohort mainly relied on the national population registry. In order to improve the follow-u, a series of additional checks were conducted: in the files of the Czech and Slovak Pensions Offices, by local enquires, and by direct correspondence. These additional efforts resulted in an increase of more than 10% in the numbers of known men to have died or emigrated. An exceptional feature of the S study is the large number of measurements of radon concentrations made in each mine-shaft (mean number per year and shaft was 223 in the period 1949-1960). Each man`s annual exposures to radon progeny in terms of working levels were estimated combining measurement data with men`s employment details. The excess relative risk models were used in the form RR = c(1 + ERR(w,x)), where ERR is excess relative risk, w and x denote exposure history and modifying variable, and c is an intercept term that allows the mortality rate for `unexposed` cohort to differ from that in the general population. The increased mortality (O/E=1.58; where O is observed and E is expected cases among collected death cases in the cohort) in the cohort, generally, somewhat lower ratios than one reflect the non-industrial character of the region, with the exception of lung cancer in man. The differences in the O/E ratios for lung cancer among the separate communities indicate that even in the situation of generally lower mortality, the dependence of lung cancer mortality on radon exposure cannot be excluded. 3 tabs., 6 refs.

Lung cancer risk models from experimental animals

International Nuclear Information System (INIS)

Gilbert, E.S.

1988-03-01

The objective of this paper is to present analyses of data based on methods that adequately account for time-related factors and competiting risks, and that yield results that are expressed in a form comparable to results obtained from recent analyses of epidemiological studies of humans exposed to radon and radon daughters. These epidemiological analyses have modeled the hazard, or age-specific death rates, as a function of factors such as dose and dose rate, time from exposure, and time from cessation of exposure. The starting point for many of the analyses of human data has been the constant relative risk modeling which the age-specific death rates are assumed to be a function of cumulative dose, and the risks due to exposure are assumed to be proportional to the age-specific baseline death rates. However, departures from this initial model, such as dependence of risks on age at risk and/or time from exposure, have been investigated. These analyses have frequently been based on a non-parametric model that requires minimal assumptions regarding the baseline risks and their dependence on age

Estimating radiation-induced cancer risk using MVK two-stage model for carcinogenesis

International Nuclear Information System (INIS)

Kai, M.; Kusama, T.; Aoki, Y.

1993-01-01

Based on the carcinogenesis model as proposed by Moolgavkar et al., time-dependent relative risk models were derived for projecting the time variation in excess relative risk. If it is assumed that each process is described by time-independent linear dose-response relationship, the time variation in excess relative risk is influenced by the parameter related with the promotion process. The risk model based carcinogenesis theory would play a marked role in estimating radiation-induced cancer risk in constructing a projection model or transfer model

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities.

Science.gov (United States)

Bobb, Jennifer F; Dominici, Francesca; Peng, Roger D

2011-12-01

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models. © 2011, The International Biometric Society.

Absolute risk, absolute risk reduction and relative risk

Directory of Open Access Journals (Sweden)

Jose Andres Calvache

2012-12-01

Full Text Available This article illustrates the epidemiological concepts of absolute risk, absolute risk reduction and relative risk through a clinical example. In addition, it emphasizes the usefulness of these concepts in clinical practice, clinical research and health decision-making process.

The Tripartite Model of Risk Perception (TRIRISK): Distinguishing Deliberative, Affective, and Experiential Components of Perceived Risk.

Science.gov (United States)

Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal

2016-10-01

Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.

Mortality Risk Prediction in Scleroderma-Related Interstitial Lung Disease: The SADL Model.

Science.gov (United States)

Morisset, Julie; Vittinghoff, Eric; Elicker, Brett M; Hu, Xiaowen; Le, Stephanie; Ryu, Jay H; Jones, Kirk D; Haemel, Anna; Golden, Jeffrey A; Boin, Francesco; Ley, Brett; Wolters, Paul J; King, Talmadge E; Collard, Harold R; Lee, Joyce S

2017-11-01

Interstitial lung disease (ILD) is an important cause of morbidity and mortality in patients with scleroderma (Scl). Risk prediction and prognostication in patients with Scl-ILD are challenging because of heterogeneity in the disease course. We aimed to develop a clinical mortality risk prediction model for Scl-ILD. Patients with Scl-ILD were identified from two ongoing longitudinal cohorts: 135 patients at the University of California, San Francisco (derivation cohort) and 90 patients at the Mayo Clinic (validation cohort). Using these two separate cohorts, a mortality risk prediction model was developed and validated by testing every potential candidate Cox model, each including three or four variables of a possible 19 clinical predictors, for time to death. Model discrimination was assessed using the C-index. Three variables were included in the final risk prediction model (SADL): ever smoking history, age, and diffusing capacity of the lung for carbon monoxide (% predicted). This continuous model had similar performance in the derivation (C-index, 0.88) and validation (C-index, 0.84) cohorts. We created a point scoring system using the combined cohort (C-index, 0.82) and used it to identify a classification with low, moderate, and high mortality risk at 3 years. The SADL model uses simple, readily accessible clinical variables to predict all-cause mortality in Scl-ILD. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

A 3-Factor Model Relating Communication to Risk Mitigation of Extended Information System Failover

Directory of Open Access Journals (Sweden)

Athanasios Podaras

2015-06-01

Full Text Available This paper aims to analyse the relation between timely and effective communication and risk mitigation of late recovery after an unexpected information system outage in enterprises. An unforeseen information system failure in modern enterprise units, may result to significant operational and financial damage. In such a critical incident, effective communication between the team leaders and the recovery team involved, can minimize or even eliminate this negative impact. An extended information system outage can be perceived as a time deviation from the Maximum Accepted Outage (ΜΑΟ timeframe, proposed by the business continuity management, according to the value of which dependent business functions may be interrupted without any serious effects to the company. The paper examines the relation between 3 basic factors and the efficient communication between team members. The factors are: timely information distribution, staff availability and network availability. Through the current paper, the author proposes a risk analysis model, based on the Composite Risk Index theory of Risk Management, which can significantly diminish the possibility of an extended information system outage, as well as calculate the extended time required to recover a system when the aforementioned factors emerge in their worst form. The precise calculation of recovery time can be achieved via the execution of business continuity tests which include scenarios, according to which an unexpected system outage coexists with delayed information distribution as well as low staff and network availability.

Concordance for prognostic models with competing risks

DEFF Research Database (Denmark)

Wolbers, Marcel; Blanche, Paul; Koller, Michael T

2014-01-01

The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate i...

Joint relative risks for estrogen receptor-positive breast cancer from a clinical model, polygenic risk score, and sex hormones.

Science.gov (United States)

Shieh, Yiwey; Hu, Donglei; Ma, Lin; Huntsman, Scott; Gard, Charlotte C; Leung, Jessica W T; Tice, Jeffrey A; Ziv, Elad; Kerlikowske, Karla; Cummings, Steven R

2017-11-01

Models that predict the risk of estrogen receptor (ER)-positive breast cancers may improve our ability to target chemoprevention. We investigated the contributions of sex hormones to the discrimination of the Breast Cancer Surveillance Consortium (BCSC) risk model and a polygenic risk score comprised of 83 single nucleotide polymorphisms. We conducted a nested case-control study of 110 women with ER-positive breast cancers and 214 matched controls within a mammography screening cohort. Participants were postmenopausal and not on hormonal therapy. The associations of estradiol, estrone, testosterone, and sex hormone binding globulin with ER-positive breast cancer were evaluated using conditional logistic regression. We assessed the individual and combined discrimination of estradiol, the BCSC risk score, and polygenic risk score using the area under the receiver operating characteristic curve (AUROC). Of the sex hormones assessed, estradiol (OR 3.64, 95% CI 1.64-8.06 for top vs bottom quartile), and to a lesser degree estrone, was most strongly associated with ER-positive breast cancer in unadjusted analysis. The BCSC risk score (OR 1.32, 95% CI 1.00-1.75 per 1% increase) and polygenic risk score (OR 1.58, 95% CI 1.06-2.36 per standard deviation) were also associated with ER-positive cancers. A model containing the BCSC risk score, polygenic risk score, and estradiol levels showed good discrimination for ER-positive cancers (AUROC 0.72, 95% CI 0.65-0.79), representing a significant improvement over the BCSC risk score (AUROC 0.58, 95% CI 0.50-0.65). Adding estradiol and a polygenic risk score to a clinical risk model improves discrimination for postmenopausal ER-positive breast cancers.

Relative and absolute risk models for cancer mortality in ankylosing spondylitis patients

International Nuclear Information System (INIS)

Muirhead, C.R.; Darby, S.C.

1989-01-01

The updated analyses presented in this paper have indicated that, even after allowing for the effects of other variables, the relative risk of all cancers excluding leukaemia and colon cancer among the irradiated spondylitics tails off beyond twenty-five years following exposure. Additionally, the corresponding absolute excess risk also tails off. This is still the only major study to show a wearing off of the radiation-related risk for such a grouping of cancers (although some wearing off has been seen for individual cancers such as bone in other studies). Further analysis of the spondylitic data (Darby, Doll and Smith, 1988) has not found any artificial explanation for the tailing off in risk, such as changes in lifestyle. However, it is noticeable that the dose was delivered to the spondylitics in fractions (see Lewis et al., 1988, table IV) rather than instantaneously, although it is not immediately obvious why this should have affected the temporal pattern of the risk. (author)

Survey of credit risk models in relation to capital adequacy framework for financial institutions

Directory of Open Access Journals (Sweden)

Poomjai Nacaskul

2016-12-01

Full Text Available This article (i iterates what is meant by credit risks and the mathematical-statistical modelling thereof, (ii elaborates the conceptual and technical links between credit risk modelling and capital adequacy framework for financial institutions, particularly as per the New Capital Accord (Basel II’s Internal Ratings-Based (IRB approach, (iii proffer a simple and intuitive taxonomy on contemporary credit risk modelling methodologies, and (iv discuses in some details a number of key models pertinent, in various stages of development, to various application areas in the banking and financial sector.

Risk and return: Long-run relations, fractional cointegration, and return predictability

DEFF Research Database (Denmark)

Bollerslev, Tim; Osterrieder, Daniela; Sizova, Natalia

2013-01-01

Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics...... are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables...

Some computer simulations based on the linear relative risk model

International Nuclear Information System (INIS)

Gilbert, E.S.

1991-10-01

This report presents the results of computer simulations designed to evaluate and compare the performance of the likelihood ratio statistic and the score statistic for making inferences about the linear relative risk mode. The work was motivated by data on workers exposed to low doses of radiation, and the report includes illustration of several procedures for obtaining confidence limits for the excess relative risk coefficient based on data from three studies of nuclear workers. The computer simulations indicate that with small sample sizes and highly skewed dose distributions, asymptotic approximations to the score statistic or to the likelihood ratio statistic may not be adequate. For testing the null hypothesis that the excess relative risk is equal to zero, the asymptotic approximation to the likelihood ratio statistic was adequate, but use of the asymptotic approximation to the score statistic rejected the null hypothesis too often. Frequently the likelihood was maximized at the lower constraint, and when this occurred, the asymptotic approximations for the likelihood ratio and score statistics did not perform well in obtaining upper confidence limits. The score statistic and likelihood ratio statistics were found to perform comparably in terms of power and width of the confidence limits. It is recommended that with modest sample sizes, confidence limits be obtained using computer simulations based on the score statistic. Although nuclear worker studies are emphasized in this report, its results are relevant for any study investigating linear dose-response functions with highly skewed exposure distributions. 22 refs., 14 tabs

Expert judgement models in quantitative risk assessment

Energy Technology Data Exchange (ETDEWEB)

Rosqvist, T. [VTT Automation, Helsinki (Finland); Tuominen, R. [VTT Automation, Tampere (Finland)

1999-12-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed.

Expert judgement models in quantitative risk assessment

International Nuclear Information System (INIS)

Rosqvist, T.; Tuominen, R.

1999-01-01

Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed

A methodology for modeling regional terrorism risk.

Science.gov (United States)

Chatterjee, Samrat; Abkowitz, Mark D

2011-07-01

Over the past decade, terrorism risk has become a prominent consideration in protecting the well-being of individuals and organizations. More recently, there has been interest in not only quantifying terrorism risk, but also placing it in the context of an all-hazards environment in which consideration is given to accidents and natural hazards, as well as intentional acts. This article discusses the development of a regional terrorism risk assessment model designed for this purpose. The approach taken is to model terrorism risk as a dependent variable, expressed in expected annual monetary terms, as a function of attributes of population concentration and critical infrastructure. This allows for an assessment of regional terrorism risk in and of itself, as well as in relation to man-made accident and natural hazard risks, so that mitigation resources can be allocated in an effective manner. The adopted methodology incorporates elements of two terrorism risk modeling approaches (event-based models and risk indicators), producing results that can be utilized at various jurisdictional levels. The validity, strengths, and limitations of the model are discussed in the context of a case study application within the United States. © 2011 Society for Risk Analysis.

MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

Directory of Open Access Journals (Sweden)

Anass BAYAGA

2010-07-01

Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

Does Implementation of Biomathematical Models Mitigate Fatigue and Fatigue-related Risks in Emergency Medical Services Operations? A Systematic Review

Science.gov (United States)

2018-01-11

Background: Work schedules like those of Emergency Medical Services (EMS) personnel have been associated with increased risk of fatigue-related impairment. Biomathematical modeling is a means of objectively estimating the potential impacts of fatigue...

A globally applicable location-specific screening model for assessing the relative risk of pesticide leaching

International Nuclear Information System (INIS)

Whelan, M.J.; Davenport, E.J.; Smith, B.G.

2007-01-01

A screening model of pesticide leaching loss is described which forms part of a multi-criteria risk-based indicator system called PRoMPT (Pesticide Risk Management and Profiling Tool). The leaching model evaluates pesticide fate in soil for any application rate and time of application (including multiple applications), for any land-based location in the world. It considers a generic evaluative environment with fixed dimensions and soil properties. The soil profile is conceptualised as a number of discrete layers. Equilibrium partitioning between adsorbed and dissolved chemical (based on the organic carbon-water partition coefficient [K OC ]) is assumed in each time step, in each layer. Non-leaching losses are described using first order kinetics. Drainage is assumed to be uniform throughout the soil profile but varies temporally. The drainage rate, which can be augmented by evapotranspiration-adjusted irrigation, is derived from long-term mean monthly water balance model calculations performed for 30 arc-minute grid cells across the entire ice-free land surface of the earth. Although, such predictions are approximate, they do capture the seasonality and relative magnitude of drainage and allow the model to be applied anywhere, without the need for extensive data compilation. PRoMPT predictions are shown to be consistent with those made by more sophisticated models (PRZM, PELMO and PEARL) for the FOCUS groundwater scenarios

A globally applicable location-specific screening model for assessing the relative risk of pesticide leaching

Energy Technology Data Exchange (ETDEWEB)

Whelan, M.J. [Unilever Safety and Environmental Assurance Centre, Colworth House, Sharnbrook, Bedfordshire, MK44 1LQ (United Kingdom)]. E-mail: mick.whelan@unilever.com; Davenport, E.J. [Unilever Safety and Environmental Assurance Centre, Colworth House, Sharnbrook, Bedfordshire, MK44 1LQ (United Kingdom); Smith, B.G. [Unilever Sustainable Agriculture Team, Colworth House, Sharnbrook, Bedfordshire, MK44 1LQ (United Kingdom)

2007-05-15

A screening model of pesticide leaching loss is described which forms part of a multi-criteria risk-based indicator system called PRoMPT (Pesticide Risk Management and Profiling Tool). The leaching model evaluates pesticide fate in soil for any application rate and time of application (including multiple applications), for any land-based location in the world. It considers a generic evaluative environment with fixed dimensions and soil properties. The soil profile is conceptualised as a number of discrete layers. Equilibrium partitioning between adsorbed and dissolved chemical (based on the organic carbon-water partition coefficient [K {sub OC}]) is assumed in each time step, in each layer. Non-leaching losses are described using first order kinetics. Drainage is assumed to be uniform throughout the soil profile but varies temporally. The drainage rate, which can be augmented by evapotranspiration-adjusted irrigation, is derived from long-term mean monthly water balance model calculations performed for 30 arc-minute grid cells across the entire ice-free land surface of the earth. Although, such predictions are approximate, they do capture the seasonality and relative magnitude of drainage and allow the model to be applied anywhere, without the need for extensive data compilation. PRoMPT predictions are shown to be consistent with those made by more sophisticated models (PRZM, PELMO and PEARL) for the FOCUS groundwater scenarios.

Non-linear models for the relation between cardiovascular risk factors and intake of wine, beer and spirits.

Science.gov (United States)

Ambler, Gareth; Royston, Patrick; Head, Jenny

2003-02-15

It is generally accepted that moderate consumption of alcohol is associated with a reduced risk of coronary heart disease (CHD). It is not clear however whether this benefit is derived through the consumption of a specific beverage type, for example, wine. In this paper the associations between known CHD risk factors and different beverage types are investigated using a novel approach with non-linear modelling. Two types of model are proposed which are designed to detect differential effects of beverage type. These may be viewed as extensions of Box and Tidwell's power-linear model. The risk factors high density lipoprotein cholesterol, fibrinogen and systolic blood pressure are considered using data from a large longitudinal study of British civil servants (Whitehall II). The results for males suggest that gram for gram of alcohol, the effect of wine differs from that of beer and spirits, particularly for systolic blood pressure. In particular increasing wine consumption is associated with slightly more favourable levels of all three risk factors studied. For females there is evidence of a differential relationship only for systolic blood pressure. These findings are tentative but suggest that further research is required to clarify the similarities and differences between the results for males and females and to establish whether either of the models is the more appropriate. However, having clarified these issues, the apparent benefit of consuming wine instead of other alcoholic beverages may be relatively small. Copyright 2003 John Wiley & Sons, Ltd.

HIV-related sexual risk behavior among African American adolescent girls.

Science.gov (United States)

Danielson, Carla Kmett; Walsh, Kate; McCauley, Jenna; Ruggiero, Kenneth J; Brown, Jennifer L; Sales, Jessica M; Rose, Eve; Wingood, Gina M; Diclemente, Ralph J

2014-05-01

Latent class analysis (LCA) is a useful statistical tool that can be used to enhance understanding of how various patterns of combined sexual behavior risk factors may confer differential levels of HIV infection risk and to identify subtypes among African American adolescent girls. Data for this analysis is derived from baseline assessments completed prior to randomization in an HIV prevention trial. Participants were African American girls (n=701) aged 14-20 years presenting to sexual health clinics. Girls completed an audio computer-assisted self-interview, which assessed a range of variables regarding sexual history and current and past sexual behavior. Two latent classes were identified with the probability statistics for the two groups in this model being 0.89 and 0.88, respectively. In the final multivariate model, class 1 (the "higher risk" group; n=331) was distinguished by a higher likelihood of >5 lifetime sexual partners, having sex while high on alcohol/drugs, less frequent condom use, and history of sexually transmitted diseases (STDs), when compared with class 2 (the "lower risk" group; n=370). The derived model correctly classified 85.3% of participants into the two groups and accounted for 71% of the variance in the latent HIV-related sexual behavior risk variable. The higher risk class also had worse scores on all hypothesized correlates (e.g., self-esteem, history of sexual assault or physical abuse) relative to the lower risk class. Sexual health clinics represent a unique point of access for HIV-related sexual risk behavior intervention delivery by capitalizing on contact with adolescent girls when they present for services. Four empirically supported risk factors differentiated higher versus lower HIV risk. Replication of these findings is warranted and may offer an empirical basis for parsimonious screening recommendations for girls presenting for sexual healthcare services.

Regional scale ecological risk assessment: using the relative risk model

National Research Council Canada - National Science Library

Landis, Wayne G

2005-01-01

...) in the performance of regional-scale ecological risk assessments. The initial chapters present the methodology and the critical nature of the interaction between risk assessors and decision makers...

Conceptual models for cumulative risk assessment.

Science.gov (United States)

Linder, Stephen H; Sexton, Ken

2011-12-01

In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects.

Cabin Environment Physics Risk Model

Science.gov (United States)

Mattenberger, Christopher J.; Mathias, Donovan Leigh

2014-01-01

This paper presents a Cabin Environment Physics Risk (CEPR) model that predicts the time for an initial failure of Environmental Control and Life Support System (ECLSS) functionality to propagate into a hazardous environment and trigger a loss-of-crew (LOC) event. This physics-of failure model allows a probabilistic risk assessment of a crewed spacecraft to account for the cabin environment, which can serve as a buffer to protect the crew during an abort from orbit and ultimately enable a safe return. The results of the CEPR model replace the assumption that failure of the crew critical ECLSS functionality causes LOC instantly, and provide a more accurate representation of the spacecraft's risk posture. The instant-LOC assumption is shown to be excessively conservative and, moreover, can impact the relative risk drivers identified for the spacecraft. This, in turn, could lead the design team to allocate mass for equipment to reduce overly conservative risk estimates in a suboptimal configuration, which inherently increases the overall risk to the crew. For example, available mass could be poorly used to add redundant ECLSS components that have a negligible benefit but appear to make the vehicle safer due to poor assumptions about the propagation time of ECLSS failures.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

Science.gov (United States)

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

Science.gov (United States)

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

Directory of Open Access Journals (Sweden)

Andrew Denovan

2017-10-01

Full Text Available The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy, the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT, the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual

Host-Country Related Risk Factors in International Construction: Meta-Analysis

Directory of Open Access Journals (Sweden)

Güzin AYDOGAN

2014-09-01

Full Text Available Internationalization has been on the agenda of construction firms as a strategic option in global competition. Due to globalization every sector including the construction industry has faced with high levels of competitiveness, uncertainty, and risk. International construction involves common risks to domestic construction, as well as risks that are related to the host country. These risks have serious effects on the performance of international projects. Since the sustainable competitiveness of international contractors depends largely on the effective management of these risks, their assessment becomes vital for the success of international contractors. The main aim of this study is to analyse the risks for international construction projects that are related to the host country. Meta-analysis technique is used in order to determine these risks. This paper, therefore, reviews the literature that has been published in four most respected construction and management journals, these being; Journal of Construction Engineering and Management, Journal of Management in Engineering, Construction Management and Economics, and International Journal of Project Management for the period of 2000-2010. International construction risk assessment models are also reviewed within the context of this study, since host country related risk factors were found to have serious effects on the profitability of international contractors due to literature review. As a result; political stability, law and regulations, exchange rate risk, cultural differences, inflation, expropriation, tax discrimination, language barrier, bribery and corruption, force majeure, and societal conflicts in the host country are found to be the most important risk factors in international construction. Findings of this study can be used in risk assessment models for international construction projects.

Building-related risk factors and work-related lower respiratory symptoms in 80 office buildings

Energy Technology Data Exchange (ETDEWEB)

Mendell, M.J.; Naco, G.M.; Wilcox, T.G.; Sieber, W.K.

2002-01-01

We assessed building-related risk factors for lower respiratory symptoms in office workers. The National Institute for Occupational Safety and Health in 1993 collected data during indoor environmental health investigations of workplaces. We used multivariate logistic regression analyses to assess relationships between lower respiratory symptoms in office workers and risk factors plausibly related to microbiologic contamination. Among 2,435 occupants in 80 office buildings, frequent, work-related multiple lower respiratory symptoms were strongly associated, in multivariate models, with two risk factors for microbiologic contamination: poor pan drainage under cooling coils and debris in outside air intake. Associations tended to be stronger among those with a history of physician-diagnosed asthma. These findings suggest that adverse lower respiratory health effects from indoor work environments, although unusual, may occur in relation to poorly designed or maintained ventilation systems, particularly among previously diagnosed asthmatics. These findings require confirmation in more representative buildings.

Building-related risk factors and work-related lower respiratory symptoms in 80 office buildings

International Nuclear Information System (INIS)

Mendell, M.J.; Naco, G.M.; Wilcox, T.G.; Sieber, W.K.

2002-01-01

We assessed building-related risk factors for lower respiratory symptoms in office workers. The National Institute for Occupational Safety and Health in 1993 collected data during indoor environmental health investigations of workplaces. We used multivariate logistic regression analyses to assess relationships between lower respiratory symptoms in office workers and risk factors plausibly related to microbiologic contamination. Among 2,435 occupants in 80 office buildings, frequent, work-related multiple lower respiratory symptoms were strongly associated, in multivariate models, with two risk factors for microbiologic contamination: poor pan drainage under cooling coils and debris in outside air intake. Associations tended to be stronger among those with a history of physician-diagnosed asthma. These findings suggest that adverse lower respiratory health effects from indoor work environments, although unusual, may occur in relation to poorly designed or maintained ventilation systems, particularly among previously diagnosed asthmatics. These findings require confirmation in more representative buildings

Association between firearm ownership, firearm-related risk and risk reduction behaviours and alcohol-related risk behaviours.

Science.gov (United States)

Wintemute, Garen J

2011-12-01

Alcohol use and firearm ownership are risk factors for violent injury and death. To determine whether firearm ownership and specific firearm-related behaviours are associated with alcohol-related risk behaviours, the author conducted a cross-sectional study using Behavioral Risk Factor Surveillance System data for eight states in the USA from 1996 to 1997 (the most recent data available). Altogether, 15 474 respondents provided information on firearm exposure. After adjustment for demographics and state of residence, firearm owners were more likely than those with no firearms at home to have ≥5 drinks on one occasion (OR 1.32; 95% CI 1.16 to 1.50), to drink and drive (OR 1.79; 95% CI 1.34 to 2.39) and to have ≥60 drinks per month (OR 1.45; 95% CI 1.14 to 1.83). Heavy alcohol use was most common among firearm owners who also engaged in behaviours such as carrying a firearm for protection against other people and keeping a firearm at home that was both loaded and not locked away. The author concludes that firearm ownership and specific firearm-related behaviours are associated with alcohol-related risk behaviours.

Urban-hazard risk analysis: mapping of heat-related risks in the elderly in major Italian cities.

Science.gov (United States)

Morabito, Marco; Crisci, Alfonso; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Di Stefano, Valentina; Orlandini, Simone; Gensini, Gian Franco

2015-01-01

Short-term impacts of high temperatures on the elderly are well known. Even though Italy has the highest proportion of elderly citizens in Europe, there is a lack of information on spatial heat-related elderly risks. Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥ 65). A long time-series (2001-2013) of remote sensing MODIS data, averaged over the summer period for eleven major Italian cities, were downscaled to obtain high spatial resolution (100 m) daytime and night-time land surface temperatures (LST). LST was estimated pixel-wise by applying two statistical model approaches: 1) the Linear Regression Model (LRM); 2) the Generalized Additive Model (GAM). Total and elderly population density data were extracted from the Joint Research Centre population grid (100 m) from the 2001 census (Eurostat source), and processed together using "Crichton's Risk Triangle" hazard-risk methodology for obtaining a Heat-related Elderly Risk Index (HERI). The GAM procedure allowed for improved daytime and night-time LST estimations compared to the LRM approach. High-resolution maps of daytime and night-time HERI levels were developed for inland and coastal cities. Urban areas with the hazardous HERI level (very high risk) were not necessarily characterized by the highest temperatures. The hazardous HERI level was generally localized to encompass the city-centre in inland cities and the inner area in coastal cities. The two most dangerous HERI levels were greater in the coastal rather than inland cities. This study shows the great potential of combining geospatial technologies and spatial demographic characteristics within a simple and flexible framework in order to provide high-resolution urban mapping of daytime and night-time HERI. In this way, potential areas for intervention are immediately identified with up-to-street level details. This information could support public health operators and facilitate coordination for heat-related

Urban-hazard risk analysis: mapping of heat-related risks in the elderly in major Italian cities.

Directory of Open Access Journals (Sweden)

Marco Morabito

Full Text Available Short-term impacts of high temperatures on the elderly are well known. Even though Italy has the highest proportion of elderly citizens in Europe, there is a lack of information on spatial heat-related elderly risks.Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥ 65.A long time-series (2001-2013 of remote sensing MODIS data, averaged over the summer period for eleven major Italian cities, were downscaled to obtain high spatial resolution (100 m daytime and night-time land surface temperatures (LST. LST was estimated pixel-wise by applying two statistical model approaches: 1 the Linear Regression Model (LRM; 2 the Generalized Additive Model (GAM. Total and elderly population density data were extracted from the Joint Research Centre population grid (100 m from the 2001 census (Eurostat source, and processed together using "Crichton's Risk Triangle" hazard-risk methodology for obtaining a Heat-related Elderly Risk Index (HERI.The GAM procedure allowed for improved daytime and night-time LST estimations compared to the LRM approach. High-resolution maps of daytime and night-time HERI levels were developed for inland and coastal cities. Urban areas with the hazardous HERI level (very high risk were not necessarily characterized by the highest temperatures. The hazardous HERI level was generally localized to encompass the city-centre in inland cities and the inner area in coastal cities. The two most dangerous HERI levels were greater in the coastal rather than inland cities.This study shows the great potential of combining geospatial technologies and spatial demographic characteristics within a simple and flexible framework in order to provide high-resolution urban mapping of daytime and night-time HERI. In this way, potential areas for intervention are immediately identified with up-to-street level details. This information could support public health operators and facilitate coordination for heat-related

A Probabilistic Typhoon Risk Model for Vietnam

Science.gov (United States)

Haseemkunju, A.; Smith, D. F.; Brolley, J. M.

2017-12-01

Annually, the coastal Provinces of low-lying Mekong River delta region in the southwest to the Red River Delta region in Northern Vietnam is exposed to severe wind and flood risk from landfalling typhoons. On average, about two to three tropical cyclones with a maximum sustained wind speed of >=34 knots make landfall along the Vietnam coast. Recently, Typhoon Wutip (2013) crossed Central Vietnam as a category 2 typhoon causing significant damage to properties. As tropical cyclone risk is expected to increase with increase in exposure and population growth along the coastal Provinces of Vietnam, insurance/reinsurance, and capital markets need a comprehensive probabilistic model to assess typhoon risk in Vietnam. In 2017, CoreLogic has expanded the geographical coverage of its basin-wide Western North Pacific probabilistic typhoon risk model to estimate the economic and insured losses from landfalling and by-passing tropical cyclones in Vietnam. The updated model is based on 71 years (1945-2015) of typhoon best-track data and 10,000 years of a basin-wide simulated stochastic tracks covering eight countries including Vietnam. The model is capable of estimating damage from wind, storm surge and rainfall flooding using vulnerability models, which relate typhoon hazard to building damageability. The hazard and loss models are validated against past historical typhoons affecting Vietnam. Notable typhoons causing significant damage in Vietnam are Lola (1993), Frankie (1996), Xangsane (2006), and Ketsana (2009). The central and northern coastal provinces of Vietnam are more vulnerable to wind and flood hazard, while typhoon risk in the southern provinces are relatively low.

Decreasing relative risk premium

DEFF Research Database (Denmark)

Hansen, Frank

2007-01-01

such that the corresponding relative risk premium is a decreasing function of present wealth, and we determine the set of associated utility functions. We find a new characterization of risk vulnerability and determine a large set of utility functions, closed under summation and composition, which are both risk vulnerable...

Events per variable for risk differences and relative risks using pseudo-observations

DEFF Research Database (Denmark)

Hansen, Stefan Nygaard; Andersen, Per Kragh; Parner, Erik Thorlund

2014-01-01

A method based on pseudo-observations has been proposed for direct regression modeling of functionals of interest with right-censored data, including the survival function, the restricted mean and the cumulative incidence function in competing risks. The models, once the pseudo-observations have...... been computed, can be fitted using standard generalized estimating equation software. Regression models can however yield problematic results if the number of covariates is large in relation to the number of events observed. Guidelines of events per variable are often used in practice. These rules...

Information risk and security modeling

Science.gov (United States)

Zivic, Predrag

2005-03-01

This research paper presentation will feature current frameworks to addressing risk and security modeling and metrics. The paper will analyze technical level risk and security metrics of Common Criteria/ISO15408, Centre for Internet Security guidelines, NSA configuration guidelines and metrics used at this level. Information IT operational standards view on security metrics such as GMITS/ISO13335, ITIL/ITMS and architectural guidelines such as ISO7498-2 will be explained. Business process level standards such as ISO17799, COSO and CobiT will be presented with their control approach to security metrics. Top level, the maturity standards such as SSE-CMM/ISO21827, NSA Infosec Assessment and CobiT will be explored and reviewed. For each defined level of security metrics the research presentation will explore the appropriate usage of these standards. The paper will discuss standards approaches to conducting the risk and security metrics. The research findings will demonstrate the need for common baseline for both risk and security metrics. This paper will show the relation between the attribute based common baseline and corporate assets and controls for risk and security metrics. IT will be shown that such approach spans over all mentioned standards. The proposed approach 3D visual presentation and development of the Information Security Model will be analyzed and postulated. Presentation will clearly demonstrate the benefits of proposed attributes based approach and defined risk and security space for modeling and measuring.

Risk factors of age-related macular degeneration in Argentina

Directory of Open Access Journals (Sweden)

María Eugenia Nano

2013-04-01

Full Text Available PURPOSES: To assess the risk factors of age-related macular degeneration in Argentina using a case-control study. METHODS: Surveys were used for subjects' antioxidant intake, age/gender, race, body mass index, hypertension, diabetes (and type of treatment, smoking, sunlight exposure, red meat consumption, fish consumption, presence of age-related macular degeneration and family history of age-related macular degeneration. Main effects models for logistic regression and ordinal logistic regression were used to analyze the results. RESULTS: There were 175 cases and 175 controls with a mean age of 75.4 years and 75.5 years, respectively, of whom 236 (67.4% were female. Of the cases with age-related macular degeneration, 159 (45.4% had age-related macular degeneration in their left eyes, 154 (44.0% in their right eyes, and 138 (39.4% in both eyes. Of the cases with age-related macular degeneration in their left eyes, 47.8% had the dry type, 40.3% had the wet type, and the type was unknown for 11.9%. The comparable figures for right eyes were: 51.9%, 34.4%, and 13.7%, respectively. The main effects model was dominated by higher sunlight exposure (OR [odds ratio]: 3.3 and a family history of age-related macular degeneration (OR: 4.3. Other factors included hypertension (OR: 2.1, smoking (OR: 2.2, and being of the Mestizo race, which lowered the risk of age-related macular degeneration (OR: 0.40. Red meat/fish consumption, body mass index, and iris color did not have an effect. Higher age was associated with progression to more severe age-related macular degeneration. CONCLUSION: Sunlight exposure, family history of age-related macular degeneration, and an older age were the significant risk factors. There may be other variables, as the risk was not explained very well by the existing factors. A larger sample may produce different and better results.

Urban-Hazard Risk Analysis: Mapping of Heat-Related Risks in the Elderly in Major Italian Cities

Science.gov (United States)

Morabito, Marco; Crisci, Alfonso; Gioli, Beniamino; Gualtieri, Giovanni; Toscano, Piero; Di Stefano, Valentina; Orlandini, Simone; Gensini, Gian Franco

2015-01-01

Background Short-term impacts of high temperatures on the elderly are well known. Even though Italy has the highest proportion of elderly citizens in Europe, there is a lack of information on spatial heat-related elderly risks. Objectives Development of high-resolution, heat-related urban risk maps regarding the elderly population (≥65). Methods A long time-series (2001–2013) of remote sensing MODIS data, averaged over the summer period for eleven major Italian cities, were downscaled to obtain high spatial resolution (100 m) daytime and night-time land surface temperatures (LST). LST was estimated pixel-wise by applying two statistical model approaches: 1) the Linear Regression Model (LRM); 2) the Generalized Additive Model (GAM). Total and elderly population density data were extracted from the Joint Research Centre population grid (100 m) from the 2001 census (Eurostat source), and processed together using “Crichton’s Risk Triangle” hazard-risk methodology for obtaining a Heat-related Elderly Risk Index (HERI). Results The GAM procedure allowed for improved daytime and night-time LST estimations compared to the LRM approach. High-resolution maps of daytime and night-time HERI levels were developed for inland and coastal cities. Urban areas with the hazardous HERI level (very high risk) were not necessarily characterized by the highest temperatures. The hazardous HERI level was generally localized to encompass the city-centre in inland cities and the inner area in coastal cities. The two most dangerous HERI levels were greater in the coastal rather than inland cities. Conclusions This study shows the great potential of combining geospatial technologies and spatial demographic characteristics within a simple and flexible framework in order to provide high-resolution urban mapping of daytime and night-time HERI. In this way, potential areas for intervention are immediately identified with up-to-street level details. This information could support public

Model linear absolute and relative risk estimates for cancer induced by ionizing radiation in Mexican cohort of occupationally exposed

International Nuclear Information System (INIS)

Alvarez, R.J.T.; Trovar, M.V.M; González, J.F.

2015-01-01

From the rate of natural mortality m s cancer (t) for every 100 thousand habitants, modeled by a fourth-degree polynomial function of the age data of the Mexican population (2008), and assuming: a) a relationship 1: 5 of cancer induced radiation respect to presented spontaneously, b) a size of initial cohort No = 100 k SOPs, c) a speed of H E = (2 ± 1) mSv / received by the SOPs from 18 to 65 years, d) a latency of 8 years for cancer induction after irradiation, e) a time tracking cohort to 75 years, f) and taking the coefficients absolute and relative risk BEIRs induction of cancer models II and VII (excluding leukemia); It determined: BEIR II for a total of 125 and 400 deaths from cancer for absolute and relative linear models respectively. For BEIR VII has a number of fatal cases of 345 and 927 deaths respectively for absolute and relative linear model cancer. [es

Vitamin E and risk of age-related cataract: a meta-analysis.

Science.gov (United States)

Zhang, Yufei; Jiang, Wenjie; Xie, Zhutian; Wu, Wenlong; Zhang, Dongfeng

2015-10-01

We conducted a meta-analysis to evaluate the relationship between vitamin E and age-related cataract (ARC). The fixed- or random-effect model was selected based on heterogeneity. Meta-regression was used to explore potential sources of between-study heterogeneity. Publication bias was evaluated using Begg's test. The dose-response relationship was assessed by a restricted cubic spline model. Relevant studies were identified by a search of PubMed and the Cochrane Library to May 2014, without language restrictions. Studies involved samples of people of all ages. Dietary vitamin E intake, dietary and supplemental vitamin E intake, and high serum tocopherol levels were significantly associated with decreased risk of ARC, the pooled relative risk was 0·73 (95% CI 0·58, 0·92), 0·86 (95% CI 0·75, 0·99) and 0·77 (95% CI 0·66, 0·91), respectively. Supplemental vitamin E intake was non-significantly associated with ARC risk (relative risk=0·92; 95% CI 0·78, 1·07). The findings from dose-response analysis showed evidence of a non-linear association between dietary vitamin E intake and ARC. The risk of ARC decreased with dietary vitamin E intake from 7 mg/d (relative risk=0·94; 95% CI 0·90, 0·97). The findings of the meta-analysis indicated that dietary vitamin E intake, dietary and supplemental vitamin E intake, and high level of serum tocopherol might be significantly associated with reduced ARC risk.

Anesthesiologist- and System-Related Risk Factors for Risk-Adjusted Pediatric Anesthesia-Related Cardiac Arrest.

Science.gov (United States)

Zgleszewski, Steven E; Graham, Dionne A; Hickey, Paul R; Brustowicz, Robert M; Odegard, Kirsten C; Koka, Rahul; Seefelder, Christian; Navedo, Andres T; Randolph, Adrienne G

2016-02-01

Pediatric anesthesia-related cardiac arrest (ARCA) is an uncommon but potentially preventable adverse event. Infants and children with more severe underlying disease are at highest risk. We aimed to identify system- and anesthesiologist-related risk factors for ARCA. We analyzed a prospectively collected patient cohort data set of anesthetics administered from 2000 to 2011 to children at a large tertiary pediatric hospital. Pre-procedure systemic disease level was characterized by ASA physical status (ASA-PS). Two reviewers independently reviewed cardiac arrests and categorized their anesthesia relatedness. Factors associated with ARCA in the univariate analyses were identified for reevaluation after adjustment for patient age and ASA-PS. Cardiac arrest occurred in 142 of 276,209 anesthetics (incidence 5.1/10,000 anesthetics); 72 (2.6/10,000 anesthetics) were classified as anesthesia-related. In the univariate analyses, risk of ARCA was much higher in cardiac patients and for anesthesiologists with lower annual caseload and/or fewer annual days delivering anesthetics (all P risk adjustment for ASA-PS ≥ III and age ≤ 6 months, however, the association with lower annual days delivering anesthetics remained (P = 0.03), but the other factors were no longer significant. Case-mix explained most associations between higher risk of pediatric ARCA and anesthesiologist-related variables at our institution, but the association with fewer annual days delivering anesthetics remained. Our findings highlight the need for rigorous adjustment for patient risk factors in anesthesia patient safety studies.

Risk Decision Making Model for Reservoir Floodwater resources Utilization

Science.gov (United States)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

Breast cancer risks and risk prediction models.

Science.gov (United States)

Engel, Christoph; Fischer, Christine

2015-02-01

BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

Risk Aversion Relates to Cognitive Ability

DEFF Research Database (Denmark)

Andersson, Ola; Holm, Håkan J.; Tyran, Jean-Robert Karl

2016-01-01

Recent experimental studies suggest that risk aversion is negatively related to cognitive ability. In this paper we report evidence that this relation might be spurious. We recruit a large subject pool drawn from the general Danish population for our experiment. By presenting subjects with choice...... tasks that vary the bias induced by random choices, we are able to generate both negative and positive correlations between risk aversion and cognitive ability. Structural estimation allowing for heterogeneity of noise yields no significant relation between risk aversion and cognitive ability. Our...... results suggest that cognitive ability is related to random decision making, rather than to risk preferences....

Risk aversion relates to cognitive ability

DEFF Research Database (Denmark)

Andersson, Ola; Holm, Håkan J.; Tyran, Jean-Robert Karl

Recent experimental studies suggest that risk aversion is negatively related to cognitive ability. In this paper we report evidence that this relation might be spurious. We recruit a large subject pool drawn from the general Danish population for our experiment. By presenting subjects with choice...... tasks that vary the bias induced by random choices, we are able to generate both negative and positive correlations between risk aversion and cognitive ability. Structural estimation allowing for heterogeneity of noise yields no significant relation between risk aversion and cognitive ability. Our...... results suggest that cognitive ability is related to random decision making rather than to risk preferences....

Modeling Exposure to Persistent Chemicals in Hazard and Risk Assessment

Energy Technology Data Exchange (ETDEWEB)

Cowan-Ellsberry, Christina E.; McLachlan, Michael S.; Arnot, Jon A.; MacLeod, Matthew; McKone, Thomas E.; Wania, Frank

2008-11-01

Fate and exposure modeling has not thus far been explicitly used in the risk profile documents prepared to evaluate significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of POP and PBT chemicals in the environment. The goal of this paper is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include: (1) Benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk. (2) Directly estimating the exposure of the environment, biota and humans to provide information to complement measurements, or where measurements are not available or are limited. (3) To identify the key processes and chemical and/or environmental parameters that determine the exposure; thereby allowing the effective prioritization of research or measurements to improve the risk profile. (4) Predicting future time trends including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and whether the assumptions and input data are relevant in the context of the application

Recursive inter-generational utility in global climate risk modeling

Energy Technology Data Exchange (ETDEWEB)

Minh, Ha-Duong [Centre International de Recherche sur l' Environnement et le Developpement (CIRED-CNRS), 75 - Paris (France); Treich, N. [Institut National de Recherches Agronomiques (INRA-LEERNA), 31 - Toulouse (France)

2003-07-01

This paper distinguishes relative risk aversion and resistance to inter-temporal substitution in climate risk modeling. Stochastic recursive preferences are introduced in a stylized numeric climate-economy model using preliminary IPCC 1998 scenarios. It shows that higher risk aversion increases the optimal carbon tax. Higher resistance to inter-temporal substitution alone has the same effect as increasing the discount rate, provided that the risk is not too large. We discuss implications of these findings for the debate upon discounting and sustainability under uncertainty. (author)

Risk terrain modeling predicts child maltreatment.

Science.gov (United States)

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adapting the Information-Motivation-Behavioral Skills Model: Predicting HIV-Related Sexual Risk among Sexual Minority Youth

Science.gov (United States)

Fisher, Colleen M.

2012-01-01

Young sexual minority males are among those at highest risk for HIV infection, yet we know relatively little about the impact of sexual identity development on HIV risk. This study used cross-sectional data to investigate factors associated with HIV-related sexual risk among a sample of sexual minority males (n = 156), ages 14 to 21 years, using…

Risk prediction model: Statistical and artificial neural network approach

Science.gov (United States)

Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

2017-04-01

Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

Fuel related risks; Braenslerisker

Energy Technology Data Exchange (ETDEWEB)

Englund, Jessica; Sernhed, Kerstin; Nystroem, Olle; Graveus, Frank (Grontmij AB, (Sweden))

2012-02-15

The project, within which this work report was prepared, aimed to complement the Vaermeforsk publication 'Handbook of fuels' on fuel related risks and measures to reduce the risks. The fuels examined in this project where the fuels included in the first version of the handbook from 2005 plus four additional fuels that will be included in the second and next edition of the handbook. Following fuels were included: woodfuels (sawdust, wood chips, powder, briquettes), slash, recycled wood, salix, bark, hardwood, stumps, straw, reed canary grass, hemp, cereal, cereal waste, olive waste, cocoa beans, citrus waste, shea, sludge, forest industrial sludge, manure, Paper Wood Plastic, tyre, leather waste, cardboard rejects, meat and bone meal, liquid animal and vegetable wastes, tall oil pitch, peat, residues from food industry, biomal (including slaughterhouse waste) and lignin. The report includes two main chapters; a general risk chapter and a chapter of fuel specific risks. The first one deals with the general concept of risk, it highlights laws and rules relevant for risk management and it discuss general risks that are related to the different steps of fuel handling, i.e. unloading, storing, processing the fuel, transportation within the facility, combustion and handling of ashes. The information that was used to produce this chapter was gathered through a literature review, site visits, and the project group's experience from risk management. The other main chapter deals with fuel-specific risks and the measures to reduce the risks for the steps of unloading, storing, processing the fuel, internal transportation, combustion and handling of the ashes. Risks and measures were considered for all the biofuels included in the second version in the handbook of fuels. Information about the risks and risk management was gathered through interviews with people working with different kinds of fuels in electricity and heat plants in Sweden. The information from

Relative risk of visceral leishmaniasis in Brazil: a spatial analysis in urban area.

Directory of Open Access Journals (Sweden)

Valdelaine Etelvina Miranda de Araújo

2013-11-01

Full Text Available BACKGROUND: Visceral leishmaniasis (VL is a vector-borne disease whose factors involved in transmission are poorly understood, especially in more urban and densely populated counties. In Brazil, the VL urbanization is a challenge for the control program. The goals were to identify the greater risk areas for human VL and the risk factors involved in transmission. METHODOLOGY: This is an ecological study on the relative risk of human VL. Spatial units of analysis were the coverage areas of the Basic Health Units (146 small-areas of Belo Horizonte, Minas Gerais State, Brazil. Human VL cases, from 2007 to 2009 (n = 412, were obtained in the Brazilian Reportable Disease Information System. Bayesian approach was used to model the relative risk of VL including potential risk factors involved in transmission (canine infection, socioeconomic and environmental features and to identify the small-areas of greater risk to human VL. PRINCIPAL FINDINGS: The relative risk of VL was shown to be correlated with income, education, and the number of infected dogs per inhabitants. The estimates of relative risk of VL were higher than 1.0 in 54% of the areas (79/146. The spatial modeling highlighted 14 areas with the highest relative risk of VL and 12 of them are concentrated in the northern region of the city. CONCLUSIONS: The spatial analysis used in this study is useful for the identification of small-areas according to risk of human VL and presents operational applicability in control and surveillance program in an urban environment with an unequal spatial distribution of the disease. Thus the frequent monitoring of relative risk of human VL in small-areas is important to direct and prioritize the actions of the control program in urban environment, especially in big cities.

A method for determining weights for excess relative risk and excess absolute risk when applied in the calculation of lifetime risk of cancer from radiation exposure

Energy Technology Data Exchange (ETDEWEB)

Walsh, Linda [Federal Office for Radiation Protection, Department of Radiation Protection and Health, Oberschleissheim (Germany); University of Manchester, The Faculty of Medical and Human Sciences, Manchester (United Kingdom); Schneider, Uwe [University of Zurich, Vetsuisse Faculty, Zurich (Switzerland); Radiotherapy Hirslanden AG, Aarau (Switzerland)

2013-03-15

Radiation-related risks of cancer can be transported from one population to another population at risk, for the purpose of calculating lifetime risks from radiation exposure. Transfer via excess relative risks (ERR) or excess absolute risks (EAR) or a mixture of both (i.e., from the life span study (LSS) of Japanese atomic bomb survivors) has been done in the past based on qualitative weighting. Consequently, the values of the weights applied and the method of application of the weights (i.e., as additive or geometric weighted means) have varied both between reports produced at different times by the same regulatory body and also between reports produced at similar times by different regulatory bodies. Since the gender and age patterns are often markedly different between EAR and ERR models, it is useful to have an evidence-based method for determining the relative goodness of fit of such models to the data. This paper identifies a method, using Akaike model weights, which could aid expert judgment and be applied to help to achieve consistency of approach and quantitative evidence-based results in future health risk assessments. The results of applying this method to recent LSS cancer incidence models are that the relative EAR weighting by cancer solid cancer site, on a scale of 0-1, is zero for breast and colon, 0.02 for all solid, 0.03 for lung, 0.08 for liver, 0.15 for thyroid, 0.18 for bladder and 0.93 for stomach. The EAR weighting for female breast cancer increases from 0 to 0.3, if a generally observed change in the trend between female age-specific breast cancer incidence rates and attained age, associated with menopause, is accounted for in the EAR model. Application of this method to preferred models from a study of multi-model inference from many models fitted to the LSS leukemia mortality data, results in an EAR weighting of 0. From these results it can be seen that lifetime risk transfer is most highly weighted by EAR only for stomach cancer. However

Evaluation of Cyber Security and Modelling of Risk Propagation with Petri Nets

Directory of Open Access Journals (Sweden)

Marcin Szpyrka

2017-02-01

Full Text Available This article presents a new method of risk propagation among associated elements. On thebasis of coloured Petri nets, a new class called propagation nets is defined. This class providesa formal model of a risk propagation. The proposed method allows for model relations betweennodes forming the network structure. Additionally, it takes into account the bidirectional relationsbetween components as well as relations between isomorphic, symmetrical components in variousbranches of the network. This method is agnostic in terms of use in various systems and it canbe adapted to the propagation model of any systems’ characteristics; however, it is intentionallyproposed to assess the risk of critical infrastructures. In this paper, as a proof of concept example, weshow the formal model of risk propagation proposed within the project Cyberspace Security ThreatsEvaluation System of the Republic of Poland. In the article, the idea of the method is presented aswell as its use case for evaluation of risk for cyber threats. With the adaptation of Petri nets, it ispossible to evaluate the risk for the particular node and assess the impact of this risk for all relatednodes including hierarchic relations of components as well as isomorphism of elements.

Construction of Site Risk Model using Individual Unit Risk Model in a NPP Site

Energy Technology Data Exchange (ETDEWEB)

Lim, Ho Gon; Han, Sang Hoon [KAERI, Daejeon (Korea, Republic of)

2016-05-15

Since Fukushima accident, strong needs to estimate site risk has been increased to identify the possibility of re-occurrence of such a tremendous disaster and prevent such a disaster. Especially, in a site which has large fleet of nuclear power plants, reliable site risk assessment is very emergent to confirm the safety. In Korea, there are several nuclear power plant site which have more than 6 NPPs. In general, risk model of a NPP in terms of PSA is very complicated and furthermore, it is expected that the site risk model is more complex than that. In this paper, the method for constructing site risk model is proposed by using individual unit risk model. Procedure for the development of site damage (risk) model was proposed in the present paper. Since the site damage model is complicated in the sense of the scale of the system and dependency of the components of the system, conventional method may not be applicable in many side of the problem.

Modeling exposure to persistent chemicals in hazard and risk assessment.

Science.gov (United States)

Cowan-Ellsberry, Christina E; McLachlan, Michael S; Arnot, Jon A; Macleod, Matthew; McKone, Thomas E; Wania, Frank

2009-10-01

Fate and exposure modeling has not, thus far, been explicitly used in the risk profile documents prepared for evaluating the significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of persistent organic pollutants (POP) and persistent, bioaccumulative, and toxic (PBT) chemicals in the environment. The goal of this publication is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include 1) benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk; 2) directly estimating the exposure of the environment, biota, and humans to provide information to complement measurements or where measurements are not available or are limited; 3) to identify the key processes and chemical or environmental parameters that determine the exposure, thereby allowing the effective prioritization of research or measurements to improve the risk profile; and 4) forecasting future time trends, including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and

Conformists or Rebels? Relative Risk Aversion, Educational Decisions, and Social Class Reproduction

DEFF Research Database (Denmark)

Holm, Anders; Jæger, Mads Meier

2012-01-01

This paper tests the theory of Relative Risk Aversion (RRA), which argues that educational decisions are intended to minimize the risk of downward social class mobility. We propose a structural model which distinguishes the instantaneous utility of educational decisions from the future utility...

Risk-based systems analysis for emerging technologies: Applications of a technology risk assessment model to public decision making

International Nuclear Information System (INIS)

Quadrel, M.J.; Fowler, K.M.; Cameron, R.; Treat, R.J.; McCormack, W.D.; Cruse, J.

1995-01-01

The risk-based systems analysis model was designed to establish funding priorities among competing technologies for tank waste remediation. The model addresses a gap in the Department of Energy's (DOE's) ''toolkit'' for establishing funding priorities among emerging technologies by providing disciplined risk and cost assessments of candidate technologies within the context of a complete remediation system. The model is comprised of a risk and cost assessment and a decision interface. The former assesses the potential reductions in risk and cost offered by new technology relative to the baseline risk and cost of an entire system. The latter places this critical information in context of other values articulated by decision makers and stakeholders in the DOE system. The risk assessment portion of the model is demonstrated for two candidate technologies for tank waste retrieval (arm-based mechanical retrieval -- the ''long reach arm'') and subsurface barriers (close-coupled chemical barriers). Relative changes from the base case in cost and risk are presented for these two technologies to illustrate how the model works. The model and associated software build on previous work performed for DOE's Office of Technology Development and the former Underground Storage Tank Integrated Demonstration, and complement a decision making tool presented at Waste Management 1994 for integrating technical judgements and non-technical (stakeholder) values when making technology funding decisions

HIV/AIDS Related Knowledge and Perceived Risk Associated with ...

African Journals Online (AJOL)

Using data from the 2004 National Survey of Adolescents in Uganda, logistic regression models were fitted to examine the odds that HIV/AIDS related knowledge and perceived risk of HIV infection are associated with condom use among adolescents. After including demographic measures, findings indicated that correct ...

Custom v. Standardized Risk Models

Directory of Open Access Journals (Sweden)

Zura Kakushadze

2015-05-01

Full Text Available We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1 longer horizon risk factors (value, growth, etc. increase noise trades and trading costs; (2 arbitrary risk factors can neutralize alpha; (3 “standardized” industries are artificial and insufficiently granular; (4 normalization of style risk factors is lost for the trading universe; (5 diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building.

Prospect relativity: how choice options influence decision under risk.

Science.gov (United States)

Stewart, Neil; Chater, Nick; Stott, Henry P; Reimers, Stian

2003-03-01

In many theories of decision under risk (e.g., expected utility theory, rank-dependent utility theory, and prospect theory), the utility of a prospect is independent of other options in the choice set. The experiments presented here show a large effect of the available options, suggesting instead that prospects are valued relative to one another. The judged certainty equivalent for a prospect is strongly influenced by the options available. Similarly, the selection of a preferred prospect is strongly influenced by the prospects available. Alternative theories of decision under risk (e.g., the stochastic difference model, multialternative decision field theory, and range frequency theory), where prospects are valued relative to one another, can provide an account of these context effects.

Development and Validation of an Older Occupant Finite Element Model of a Mid-Sized Male for Investigation of Age-related Injury Risk.

Science.gov (United States)

Schoell, Samantha L; Weaver, Ashley A; Urban, Jillian E; Jones, Derek A; Stitzel, Joel D; Hwang, Eunjoo; Reed, Matthew P; Rupp, Jonathan D; Hu, Jingwen

2015-11-01

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test. The second objective was to investigate age-related injury risks by performing a frontal US NCAP simulation test with the GHBMC M50 65 YO and the GHBMC M50 v4.2 models. Simulation results were compared to the GHBMC M50 v4.2 to evaluate the effect of age on occupant response and risk for head injury, neck injury, thoracic injury, and lower extremity injury. Overall, the GHBMC M50 65 YO model predicted higher probabilities of AIS 3+ injury for the head and thorax.

Modelling the joint distribution of competing risks survival times using copula functions

OpenAIRE

Kaishev, V. K.; Haberman, S.; Dimitrova, D. S.

2005-01-01

The problem of modelling the joint distribution of survival times in a competing risks model, using copula functions is considered. In order to evaluate this joint distribution and the related overall survival function, a system of non-linear differential equations is solved, which relates the crude and net survival functions of the modelled competing risks, through the copula. A similar approach to modelling dependent multiple decrements was applied by Carriere (1994) who used a Gaussian cop...

A software quality model and metrics for risk assessment

Science.gov (United States)

Hyatt, L.; Rosenberg, L.

1996-01-01

A software quality model and its associated attributes are defined and used as the model for the basis for a discussion on risk. Specific quality goals and attributes are selected based on their importance to a software development project and their ability to be quantified. Risks that can be determined by the model's metrics are identified. A core set of metrics relating to the software development process and its products is defined. Measurements for each metric and their usability and applicability are discussed.

Mechanistic modeling of insecticide risks to breeding birds in ...

Science.gov (United States)

Insecticide usage in the United States is ubiquitous in urban, suburban, and rural environments. In evaluating data for an insecticide registration application and for registration review, scientists at the United States Environmental Protection Agency (USEPA) assess the fate of the insecticide and the risk the insecticide poses to the environment and non-target wildlife. At the present time, current USEPA risk assessments do not include population-level endpoints. In this paper, we present a new mechanistic model, which allows risk assessors to estimate the effects of insecticide exposure on the survival and seasonal productivity of birds known to use agricultural fields during their breeding season. The new model was created from two existing USEPA avian risk assessment models, the Terrestrial Investigation Model (TIM v.3.0) and the Markov Chain Nest Productivity model (MCnest). The integrated TIM/MCnest model has been applied to assess the relative risk of 12 insecticides used to control corn pests on a suite of 31 avian species known to use cornfields in midwestern agroecosystems. The 12 insecticides that were assessed in this study are all used to treat major pests of corn (corn root worm borer, cutworm, and armyworm). After running the integrated TIM/MCnest model, we found extensive differences in risk to birds among insecticides, with chlorpyrifos and malathion (organophosphates) generally posing the greatest risk, and bifenthrin and ë-cyhalothrin (

The globalization of risk and risk perception: why we need a new model of risk communication for vaccines.

Science.gov (United States)

Larson, Heidi; Brocard Paterson, Pauline; Erondu, Ngozi

2012-11-01

Risk communication and vaccines is complex and the nature of risk perception is changing, with perceptions converging, evolving and having impacts well beyond specific geographic localities and points in time, especially when amplified through the Internet and other modes of global communication. This article examines the globalization of risk perceptions and their impacts, including the example of measles and the globalization of measles, mumps and rubella (MMR) vaccine risk perceptions, and calls for a new, more holistic model of risk assessment, risk communication and risk mitigation, embedded in an ongoing process of risk management for vaccines and immunization programmes. It envisions risk communication as an ongoing process that includes trust-building strategies hand-in-hand with operational and policy strategies needed to mitigate and manage vaccine-related risks, as well as perceptions of risk.

Water security, risk and economic growth: lessons from a dynamical systems model

Science.gov (United States)

Dadson, Simon; Hall, Jim; Garrick, Dustin; Sadoff, Claudia; Grey, David; Whittington, Dale

2016-04-01

Investments in the physical infrastructure, human capital, and institutions needed for water resources management have been a noteworthy feature in the development of most civilisations. These investments affect the economy in two distinct ways: (i) by improving the factor productivity of water in multiple sectors of the economy, especially those that are water intensive such as agriculture and energy; and (ii) by reducing the acute and chronic harmful effects of water-related hazards like floods, droughts, and water-related diseases. The need for capital investment to mitigate these risks in order to promote economic growth is widely acknowledged, but prior work to conceptualise the relationship between water-related risks and economic growth has focused on the productive and harmful roles of water in the economy independently. Here the two influences are combined using a simple, dynamical model of water-related investment, risk, and growth at the national level. The model suggests the existence of a context-specific threshold above which growth proceeds along an 'S'-curve. In many cases there is a requirement for initial investment in water-related assets to enable growth. Below the threshold it is possible for a poverty trap to arise. The presence and location of the poverty trap is context-specific and depends on the relative exposure of productive water-related assets to risk, compared with risks faced by assets in the wider economy. Exogenous changes in the level of water-related risk (through, for example, climate and land cover change) can potentially push an economy away from a growth path towards a poverty trap. These results illustrate the value of accounting for environmental risk in models of economic growth and may offer guidance in the design of robust policies for investment in water-related productive assets to manage risk, particularly in the face of global and regional environmental change.

Spatiotemporal Modeling of Community Risk

Science.gov (United States)

2016-03-01

Ertugay, and Sebnem Duzgun, “Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas,” Fire ...response in communities.”26 In “Exploratory and Inferential Methods for Spatio-temporal Analysis of Residential Fire Clustering in Urban Areas,” Ceyhan...of fire resources spread across the community. Spatiotemporal modeling shows that actualized risk is dynamic and relatively patterned. Though

Risk analysis: divergent models and convergent interpretations

Science.gov (United States)

Carnes, B. A.; Gavrilova, N.

2001-01-01

Material presented at a NASA-sponsored workshop on risk models for exposure conditions relevant to prolonged space flight are described in this paper. Analyses used mortality data from experiments conducted at Argonne National Laboratory on the long-term effects of external whole-body irradiation on B6CF1 mice by 60Co gamma rays and fission neutrons delivered as a single exposure or protracted over either 24 or 60 once-weekly exposures. The maximum dose considered was restricted to 1 Gy for neutrons and 10 Gy for gamma rays. Proportional hazard models were used to investigate the shape of the dose response at these lower doses for deaths caused by solid-tissue tumors and tumors of either connective or epithelial tissue origin. For protracted exposures, a significant mortality effect was detected at a neutron dose of 14 cGy and a gamma-ray dose of 3 Gy. For single exposures, radiation-induced mortality for neutrons also occurred within the range of 10-20 cGy, but dropped to 86 cGy for gamma rays. Plots of risk relative to control estimated for each observed dose gave a visual impression of nonlinearity for both neutrons and gamma rays. At least for solid-tissue tumors, male and female mortality was nearly identical for gamma-ray exposures, but mortality risks for females were higher than for males for neutron exposures. As expected, protracting the gamma-ray dose reduced mortality risks. Although curvature consistent with that observed visually could be detected by a model parameterized to detect curvature, a relative risk term containing only a simple term for total dose was usually sufficient to describe the dose response. Although detectable mortality for the three pathology end points considered typically occurred at the same level of dose, the highest risks were almost always associated with deaths caused by tumors of epithelial tissue origin.

Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide

DEFF Research Database (Denmark)

Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete

2017-01-01

trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during......People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time...... admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors...

Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide

DEFF Research Database (Denmark)

Madsen, Trine; Erlangsen, Annette; Nordentoft, Merete

2017-01-01

People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time...... trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during...... is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment...

Towards an Empirical-Relational Model of Supply Chain Flexibility

OpenAIRE

Santanu Mandal

2015-01-01

Supply chains are prone to disruptions and associated risks. To develop capabilities for risk mitigation, supply chains need to be flexible. A flexible supply chain can respond better to environmental contingencies. Based on the theoretical tenets of resource-based view, relational view and dynamic capabilities theory, the current study develops a relational model of supply chain flexibility comprising trust, commitment, communication, co-operation, adaptation and interdependence. Subsequentl...

A nonstationary Markov transition model for computing the relative risk of dementia before death

Science.gov (United States)

Yu, Lei; Griffith, William S.; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.

2010-01-01

This paper investigates the long-term behavior of the k-step transition probability matrix for a nonstationary discrete time Markov chain in the context of modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. The authors derive formulas for the following absorption statistics: (1) the relative risk of absorption between competing absorbing states, and (2) the mean and variance of the number of visits among the transient states before absorption. Since absorption is not guaranteed, sufficient conditions are discussed to ensure that the substochastic matrix associated with transitions among transient states converges to zero in limit. Results are illustrated with an application to the Nun Study, a cohort of 678 participants, 75 to 107 years of age, followed longitudinally with up to ten cognitive assessments over a fifteen-year period. PMID:20087848

Credit Risk Modeling

DEFF Research Database (Denmark)

Lando, David

Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers...... and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand...

European Approaches to Work-Related Stress: A Critical Review on Risk Evaluation

Directory of Open Access Journals (Sweden)

Silvia Zoni

2012-03-01

Full Text Available In recent years, various international organizations have raised awareness regarding psychosocial risks and work-related stress. European stakeholders have also taken action on these issues by producing important documents, such as position papers and government regulations, which are reviewed in this article. In particular, 4 European models that have been developed for the assessment and management of work-related stress are considered here. Although important advances have been made in the understanding of work-related stress, there are still gaps in the translation of this knowledge into effective practice at the enterprise level. There are additional problems regarding the methodology in the evaluation of work-related stress. The European models described in this article are based on holistic, global and participatory approaches, where the active role of and involvement of workers are always emphasized. The limitations of these models are in the lack of clarity on preventive intervention and, for two of them, the lack of instrument standardization for risk evaluation. The comparison among the European models to approach work-related stress, although with limitations and socio-cultural differences, offers the possibility for the development of a social dialogue that is important in defining the correct and practical methodology for work stress evaluation and prevention.

European approaches to work-related stress: a critical review on risk evaluation.

Science.gov (United States)

Zoni, Silvia; Lucchini, Roberto G

2012-03-01

In recent years, various international organizations have raised awareness regarding psychosocial risks and work-related stress. European stakeholders have also taken action on these issues by producing important documents, such as position papers and government regulations, which are reviewed in this article. In particular, 4 European models that have been developed for the assessment and management of work-related stress are considered here. Although important advances have been made in the understanding of work-related stress, there are still gaps in the translation of this knowledge into effective practice at the enterprise level. There are additional problems regarding the methodology in the evaluation of work-related stress. The European models described in this article are based on holistic, global and participatory approaches, where the active role of and involvement of workers are always emphasized. The limitations of these models are in the lack of clarity on preventive intervention and, for two of them, the lack of instrument standardization for risk evaluation. The comparison among the European models to approach work-related stress, although with limitations and socio-cultural differences, offers the possibility for the development of a social dialogue that is important in defining the correct and practical methodology for work stress evaluation and prevention.

Threshold Evaluation of Emergency Risk Communication for Health Risks Related to Hazardous Ambient Temperature.

Science.gov (United States)

Liu, Yang; Hoppe, Brenda O; Convertino, Matteo

2018-04-10

Emergency risk communication (ERC) programs that activate when the ambient temperature is expected to cross certain extreme thresholds are widely used to manage relevant public health risks. In practice, however, the effectiveness of these thresholds has rarely been examined. The goal of this study is to test if the activation criteria based on extreme temperature thresholds, both cold and heat, capture elevated health risks for all-cause and cause-specific mortality and morbidity in the Minneapolis-St. Paul Metropolitan Area. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson generalized linear model is used to derive the exposure-response functions between daily maximum heat index and mortality (1998-2014) and morbidity (emergency department visits; 2007-2014). Specific causes considered include cardiovascular, respiratory, renal diseases, and diabetes. Six extreme temperature thresholds, corresponding to 1st-3rd and 97th-99th percentiles of local exposure history, are examined. All six extreme temperature thresholds capture significantly increased relative risks for all-cause mortality and morbidity. However, the cause-specific analyses reveal heterogeneity. Extreme cold thresholds capture increased mortality and morbidity risks for cardiovascular and respiratory diseases and extreme heat thresholds for renal disease. Percentile-based extreme temperature thresholds are appropriate for initiating ERC targeting the general population. Tailoring ERC by specific causes may protect some but not all individuals with health conditions exacerbated by hazardous ambient temperature exposure. © 2018 Society for Risk Analysis.

Dose related risk and effect assessment model (DREAM) -- A more realistic approach to risk assessment of offshore discharges

International Nuclear Information System (INIS)

Johnsen, S.; Furuholt, E.

1995-01-01

Risk assessment of discharges from offshore oil and gas production to the marine environment features determination of potential environmental concentration (PEC) levels and no observed effect concentration (NOEC) levels. The PEC values are normally based on dilution of chemical components in the actual discharge source in the recipient, while the NOEC values are determined by applying a safety factor to acute toxic effects from laboratory tests. The DREAM concept focuses on realistic exposure doses as function of contact time and dilution, rather than fixed exposure concentrations of chemicals in long time exposure regimes. In its present state, the DREAM model is based on a number of assumptions with respect to the link between real life exposure doses and effects observed in laboratory tests. A research project has recently been initiated to develop the concept further, with special focus on chronic effects of different chemical compounds on the marine ecosystem. One of the questions that will be addressed is the link between exposure time, dose, concentration and effect. Validation of the safety factors applied for transforming acute toxic data into NOEC values will also be included. The DREAM model has been used by Statoil for risk assessment of discharges from new and existing offshore oil and gas production fields, and has been found to give a much more realistic results than conventional risk assessment tools. The presentation outlines the background for the DREAM approach, describes the model in its present state, discusses further developments and applications, and shows a number of examples on the performance of DREAM

An Empirical Investigation of Risk-Return Relations in Chinese Equity Markets: Evidence from Aggregate and Sectoral Data

OpenAIRE

Thomas C. Chiang; Yuanqing Zhang

2018-01-01

This paper investigates the risk-return relations in Chinese equity markets. Based on a TARCH-M model, evidence shows that stock returns are positively correlated with predictable volatility, supporting the risk-return relation in both aggregate and sectoral markets. Evidence finds a positive relation between stock return and intertemporal downside risk, while controlling for sentiment and liquidity. This study suggests that the U.S. stress risk or the world downside risk should be priced int...

Risk management model in road transport systems

Science.gov (United States)

Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

2016-08-01

The article presents the results of a study of road safety indicators that influence the development and operation of the transport system. Road safety is considered as a continuous process of risk management. Authors constructed a model that relates the social risks of a major road safety indicator - the level of motorization. The model gives a fairly accurate assessment of the level of social risk for any given level of motorization. Authors calculated the dependence of the level of socio-economic costs of accidents and injured people in them. The applicability of the concept of socio-economic damage is caused by the presence of a linear relationship between the natural and economic indicators damage from accidents. The optimization of social risk is reduced to finding the extremum of the objective function that characterizes the economic effect of the implementation of measures to improve safety. The calculations make it possible to maximize the net present value, depending on the costs of improving road safety, taking into account socio-economic damage caused by accidents. The proposed econometric models make it possible to quantify the efficiency of the transportation system, allow to simulate the change in road safety indicators.

Derivation and Validation of a Risk Standardization Model for Benchmarking Hospital Performance for Health-Related Quality of Life Outcomes after Acute Myocardial Infarction

Science.gov (United States)

Arnold, Suzanne V.; Masoudi, Frederick A.; Rumsfeld, John S.; Li, Yan; Jones, Philip G.; Spertus, John A.

2014-01-01

Background Before outcomes-based measures of quality can be used to compare and improve care, they must be risk-standardized to account for variations in patient characteristics. Despite the importance of health-related quality of life (HRQL) outcomes among patients with acute myocardial infarction (AMI), no risk-standardized models have been developed. Methods and Results We assessed disease-specific HRQL using the Seattle Angina Questionnaire at baseline and 1 year later in 2693 unselected AMI patients from 24 hospitals enrolled in the TRIUMPH registry. Using 57 candidate sociodemographic, economic, and clinical variables present on admission, we developed a parsimonious, hierarchical linear regression model to predict HRQL. Eleven variables were independently associated with poor HRQL after AMI, including younger age, prior CABG, depressive symptoms, and financial difficulties (R2=20%). The model demonstrated excellent internal calibration and reasonable calibration in an independent sample of 1890 AMI patients in a separate registry, although the model slightly over-predicted HRQL scores in the higher deciles. Among the 24 TRIUMPH hospitals, 1-year unadjusted HRQL scores ranged from 67–89. After risk-standardization, HRQL scores variability narrowed substantially (range=79–83), and the group of hospital performance (bottom 20%/middle 60%/top 20%) changed in 14 of the 24 hospitals (58% reclassification with risk-standardization). Conclusions In this predictive model for HRQL after AMI, we identified risk factors, including economic and psychological characteristics, associated with HRQL outcomes. Adjusting for these factors substantially altered the rankings of hospitals as compared with unadjusted comparisons. Using this model to compare risk-standardized HRQL outcomes across hospitals may identify processes of care that maximize this important patient-centered outcome. PMID:24163068

Statistical models for competing risk analysis

International Nuclear Information System (INIS)

Sather, H.N.

1976-08-01

Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined

An Empirical Investigation of Risk-Return Relations in Chinese Equity Markets: Evidence from Aggregate and Sectoral Data

Directory of Open Access Journals (Sweden)

Thomas C. Chiang

2018-03-01

Full Text Available This paper investigates the risk-return relations in Chinese equity markets. Based on a TARCH-M model, evidence shows that stock returns are positively correlated with predictable volatility, supporting the risk-return relation in both aggregate and sectoral markets. Evidence finds a positive relation between stock return and intertemporal downside risk, while controlling for sentiment and liquidity. This study suggests that the U.S. stress risk or the world downside risk should be priced into the Chinese stocks. The paper concludes that the risk-return tradeoff is present in the GARCH-in-mean, local downside risk-return, and global risk-return relations.

Modeling risk and uncertainty in designing reverse logistics problem

Directory of Open Access Journals (Sweden)

Aida Nazari Gooran

2018-01-01

Full Text Available Increasing attention to environmental problems and social responsibility lead to appear reverse logistic (RL issues in designing supply chain which, in most recently, has received considerable attention from both academicians and practitioners. In this paper, a multi-product reverse logistic network design model is developed; then a hybrid method including Chance-constrained programming, Genetic algorithm and Monte Carlo simulation, are proposed to solve the developed model. The proposed model is solved for risk-averse and risk-seeking decision makers by conditional value at risk, sum of the excepted value and standard deviation, respectively. Comparisons of the results show that minimizing the costs had no direct relation with the kind of decision makers; however, in the most cases, risk-seeking decision maker gained more return products than risk-averse ones. It is clear that by increasing returned products to the chain, production costs of new products and material will be reduced and also by this act, environmental benefits will be created.

Testing for changes in spatial relative risk.

Science.gov (United States)

Hazelton, Martin L

2017-07-30

The spatial relative risk function is a useful tool for describing geographical variation in disease incidence. We consider the problem of comparing relative risk functions between two time periods, with the idea of detecting alterations in the spatial pattern of disease risk irrespective of whether there has been a change in the overall incidence rate. Using case-control datasets for each period, we use kernel smoothing methods to derive a test statistic based on the difference between the log-relative risk functions, which we term the log-relative risk ratio. For testing a null hypothesis of an unchanging spatial pattern of risk, we show how p-values can be computed using both randomization methods and an asymptotic normal approximation. The methodology is applied to data on campylobacteriosis from 2006 to 2013 in a region of New Zealand. We find clear evidence of a change in the spatial pattern of risk between those years, which can be explained in differences by response to a public health initiative between urban and rural communities. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Aquaplaning : Development of a Risk Pond Model from Road Surface Measurements

OpenAIRE

Nygårdhs, Sara

2003-01-01

Aquaplaning accidents are relatively rare, but could have fatal effects. The task of this master’s thesis is to use data from the Laser Road Surface Tester to detect road sections with risk of aquaplaning. A three-dimensional model based on data from road surface measurements is created using MATLAB (version 6.1). From this general geometrical model of the road, a pond model is produced from which the theoretical risk ponds are detected. A risk pond indication table is fur-ther created. The...

Work-related stress risk assessment in Italy: the validation study of health safety and executive indicator tool.

Science.gov (United States)

Rondinone, Bruna Maria; Persechino, Benedetta; Castaldi, Tiziana; Valenti, Antonio; Ferrante, Pierpaolo; Ronchetti, Matteo; Iavicoli, Sergio

2012-01-01

In compliance with the Italian occupational health and safety regulatory framework, as provided by the Lgs. Decree 81/2008, the "work-related stress" risk assessment should follow the same principles as other risk assessments, in accordance with the European Agreement of 8 October 2004; therefore, validated and scientifically proven methodological tools are needed to conduct an adequate work-related stress risk assessment. The UK's Health Safety and Executive (HSE) Indicator Tool (IT) is used for assessing the risk of work-related stress. The aim of this study is to test the factor structure of IT as a measure of work-related stress in a sample of Italian workers. Data collected from 65 Italian organizations (6378 workers) was used for a Confirmatory Factor Analysis (CFA) on the 35-item seven-factor model. The results showed acceptable fit to the data (CFI .90; TLI .89, RMSEA .045). A second CFA was done to test a 35-item six-factor model (CFI .89, TLI .87, RMSEA .047). Both models were tested after removing six items (factor loadings less than .50.), resulting in a 29-item model. Here again, there was an acceptable fit to the data (29-item seven-factor model: CFI .93, TLI .91, RMSEA .044; 29-item six-factor model: CFI .92, TLI .90, RMSEA .046). These findings show that the HSE model satisfactorily adapts to use in a sample of Italian workers. One of the most important innovations introduced in the assessment of work-related stress with the HSE IT is the global approach for identifying work-related stress risk factors, aimed at establishing the best strategy from the viewpoints of prevention officers and also of workers.

Model risk analysis for risk management and option pricing

NARCIS (Netherlands)

Kerkhof, F.L.J.

2003-01-01

Due to the growing complexity of products in financial markets, market participants rely more and more on quantitative models for trading and risk management decisions. This introduces a fairly new type of risk, namely, model risk. In the first part of this thesis we investigate the quantitative

The influence of uncertain map features on risk beliefs and perceived ambiguity for maps of modeled cancer risk from air pollution

Science.gov (United States)

Myers, Jeffrey D.

2012-01-01

Maps are often used to convey information generated by models, for example, modeled cancer risk from air pollution. The concrete nature of images, such as maps, may convey more certainty than warranted for modeled information. Three map features were selected to communicate the uncertainty of modeled cancer risk: (a) map contours appeared in or out of focus, (b) one or three colors were used, and (c) a verbal-relative or numeric risk expression was used in the legend. Study aims were to assess how these features influenced risk beliefs and the ambiguity of risk beliefs at four assigned map locations that varied by risk level. We applied an integrated conceptual framework to conduct this full factorial experiment with 32 maps that varied by the three dichotomous features and four risk levels; 826 university students participated. Data was analyzed using structural equation modeling. Unfocused contours and the verbal-relative risk expression generated more ambiguity than their counterparts. Focused contours generated stronger risk beliefs for higher risk levels and weaker beliefs for lower risk levels. Number of colors had minimal influence. The magnitude of risk level, conveyed using incrementally darker shading, had a substantial dose-response influence on the strength of risk beliefs. Personal characteristics of prior beliefs and numeracy also had substantial influences. Bottom-up and top-down information processing suggest why iconic visual features of incremental shading and contour focus had the strongest visual influences on risk beliefs and ambiguity. Variations in contour focus and risk expression show promise for fostering appropriate levels of ambiguity. PMID:22985196

Variations with time and age in the relative risks of solid cancer incidence after radiation exposure

International Nuclear Information System (INIS)

Little, M.P.; Muirhead, C.R.; de Vathaire, F.; Charles, M.W.

1997-01-01

The Japanese atomic bomb survivor cancer incidence dataset and data on five groups exposed to radiation for medical reasons in childhood are analysed and evidence found for a reduction in the radiation-induced relative risk of cancers other than leukaemia with increasing time since exposure and age at exposure. The rate of the reductions in relative risk with time since exposure are not significantly different for those exposed in childhood and for those exposed in adulthood, if adjustment is made for the effects on the relative risk of age at exposure. For those irradiated in childhood, there is a statistically significant annual reduction of 5.8% (95% Cl 2.8, 8.9) in excess relative risk, and there are no strong indications of inter-cohort heterogeniety in the speed of reduction of relative risk. After adjustment for the effects of age at exposure, there is a significant annual reduction of 3.6% (95% Cl 1.6, 5.6) in excess relative risk in all age-at-exposure groups. There are significant reductions of 5.2% (95% Cl 3.7, 6.8) in excess relative risk per year of age at exposure. There are statistically significant (P = 0.04) interactions between the exponential adjustments to the excess relative risk for age at exposure and time since exposure in the Japanese data, but no indications (P = 0.38) of such interactions when powers of time since exposure and attained age are used to adjust the excess relative risk, so that the fit of the model with power adjustments is to be preferred to that of the model with exponential adjustments. (author)

RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

Directory of Open Access Journals (Sweden)

Ming-Chang LEE

2015-07-01

Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets.  The risk analysis and asset allocation are the key technology of banking and risk management.  The aim of this paper, build a loan portfolio optimization model based on risk analysis.  Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank.  In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm.  This paper solves the highly difficult problem by matrix operation method.  Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space.  It is easy calculation in proposed method.

Are all risks equal? Early experiences of poverty-related risk and children's functioning.

Science.gov (United States)

Roy, Amanda L; Raver, C Cybele

2014-06-01

Using cumulative risk and latent class analysis (LCA) models, we examined how exposure to deep poverty (income-to-needs ratio risks (i.e., single-parent household, residential crowding, caregiver depression, and multiple life stressors) in preschool is related to children's future difficulty in school in a longitudinal sample of 602 Head Start-enrolled, low-income families. Results from the LCA revealed 4 risk profiles: low risk, deep poverty and single, single and stressed, and deep poverty and crowded household. Tests of measurement invariance across racial/ethnic groups established that, although patterns of risk are similar across groups (i.e., risks covary in the same way), the prevalence of risk profiles differs. African American families were overrepresented in the "deep poverty and single" profile while Latino and White families were overrepresented in the "deep poverty and crowded" profile. Finally, children's third grade functioning in 3 domains (i.e., academic performance, behavior problems, and self-regulatory skills) was predicted using a cumulative risk index and LCA-identified risk profiles. Both approaches demonstrated that children who experienced higher levels of risk in preschool had worse school performance than children with low levels of risk. However, LCA also revealed that children who experienced "single and stressed" family settings had more behavior problems than low-risk children while children who experienced "deep poverty and crowded" family settings had worse academic performance. The results indicate that all risks are not equal for children's development and highlight the utility of LCA for tailoring intervention efforts to best meet the needs of target populations. PsycINFO Database Record (c) 2014 APA, all rights reserved

Derivation and validation of a risk standardization model for benchmarking hospital performance for health-related quality of life outcomes after acute myocardial infarction.

Science.gov (United States)

Arnold, Suzanne V; Masoudi, Frederick A; Rumsfeld, John S; Li, Yan; Jones, Philip G; Spertus, John A

2014-01-21

Before outcomes-based measures of quality can be used to compare and improve care, they must be risk-standardized to account for variations in patient characteristics. Despite the importance of health-related quality of life (HRQL) outcomes among patients with acute myocardial infarction (AMI), no risk-standardized models have been developed. We assessed disease-specific HRQL using the Seattle Angina Questionnaire at baseline and 1 year later in 2693 unselected AMI patients from 24 hospitals enrolled in the Translational Research Investigating Underlying disparities in acute Myocardial infarction Patients' Health status (TRIUMPH) registry. Using 57 candidate sociodemographic, economic, and clinical variables present on admission, we developed a parsimonious, hierarchical linear regression model to predict HRQL. Eleven variables were independently associated with poor HRQL after AMI, including younger age, previous coronary artery bypass graft surgery, depressive symptoms, and financial difficulties (R(2)=20%). The model demonstrated excellent internal calibration and reasonable calibration in an independent sample of 1890 AMI patients in a separate registry, although the model slightly overpredicted HRQL scores in the higher deciles. Among the 24 TRIUMPH hospitals, 1-year unadjusted HRQL scores ranged from 67-89. After risk-standardization, HRQL score variability narrowed substantially (range=79-83), and the group of hospital performance (bottom 20%/middle 60%/top 20%) changed in 14 of the 24 hospitals (58% reclassification with risk-standardization). In this predictive model for HRQL after AMI, we identified risk factors, including economic and psychological characteristics, associated with HRQL outcomes. Adjusting for these factors substantially altered the rankings of hospitals as compared with unadjusted comparisons. Using this model to compare risk-standardized HRQL outcomes across hospitals may identify processes of care that maximize this important patient

[A model list of high risk drugs].

Science.gov (United States)

Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L

2013-12-01

«High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

Ecological models and pesticide risk assessment: current modeling practice.

Science.gov (United States)

Schmolke, Amelie; Thorbek, Pernille; Chapman, Peter; Grimm, Volker

2010-04-01

Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here. (c) 2010 SETAC.

Model Risk in Portfolio Optimization

Directory of Open Access Journals (Sweden)

David Stefanovits

2014-08-01

Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.

Managing risk in statistics - "Relative risk" | Durrheim | South African ...

African Journals Online (AJOL)

South African Family Practice. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 45, No 8 (2003) >. Log in or Register to get access to full text downloads. Username, Password, Remember me, or Register. Managing risk in statistics - "Relative risk". DN Durrheim ...

Risk of ovarian cancer in women with first-degree relatives with cancer

DEFF Research Database (Denmark)

Soegaard, Marie; Frederiksen, Kirsten; Jensen, Allan

2009-01-01

OBJECTIVE: To assess the risk of ovarian cancer in women with first-degree relatives with cancer at one of the four most frequent hereditary sites based on validated cancer diagnoses and to examine the association according to age at diagnosis of ovarian cancer and histology. DESIGN: Case......-control study. SETTING AND POPULATION: First-degree relatives of 554 women with invasive epithelial ovarian cancer and 1,564 controls were included. METHODS: Analyses were performed using multiple logistic regression models. RESULTS: Ovarian cancer in a first-degree relative was significantly associated...... with increased risk of ovarian cancer (OR, 2.4; 95% CI, 1.4-4.1 (mother or sister)). Ovarian cancer in a first-degree relative appeared to be a stronger risk factor for early-onset (cancer than late-onset (OR, 5.3; 95% CI, 2.0-14.1 vs. OR, 1.8; 95% CI, 1.0-3.4). The positive association...

Risk of Cardiovascular Morbidity and Mortality in Relation to Temperature

Science.gov (United States)

Mathes, Robert; Ito, Kazuhiko; Matte, Thomas

2013-01-01

Objective To examine the effects of temperature on cardiovascular-related (CVD) morbidity and mortality among New York City (NYC) residents. Introduction Extreme temperatures are consistently shown to have an effect on CVD-related mortality [1, 2]. A large multi-city study of mortality demonstrated a cold-day and hot-day weather effect on CVD-related deaths, with the larger impact occurring on the coldest days [3]. In contrast, the association between weather and CVD-related morbidity is less clear [4, 5]. The purpose of this study is to characterize the effect of temperature on CVD-related emergency department (ED) visits, hospitalizations, and mortality on a large, heterogeneous population. Additionally, we conducted a sensitivity analysis to determine the impact of air pollutants, specifically fine particulates (PM2.5) and ozone (O3), along with temperature, on CVD outcomes. Methods We analyzed daily weather conditions, ED visits classified as CVD-related based on chief complaint text, hospitalizations, and natural cause deaths that occurred in NYC between 2002 and 2006. ED visits were obtained from data reported daily to the city health department for syndromic surveillance. Inpatient admissions were obtained from the Statewide Planning and Research Cooperative System, a data reporting system developed by New York State. Mortality data were obtained from the NYC Office of Vital Statistics. Data for PM2.5 and O3 were obtained from all available air quality monitors within the five boroughs of NYC. To estimate risk of CVD morbidity and mortality, we used generalized linear models using a Poisson distribution to calculate relative risks (RR) and 95% confidence intervals (CI). A non-linear distributed lag was used to model mean temperature in order to allow for its effect on the same day and on subsequent days. Models were fit separately for cold season (October through March) and warm season (April through September) given season may modify the effect on CVD

Relative Hazard and Risk Measure Calculation Methodology Rev 1

International Nuclear Information System (INIS)

Stenner, Robert D.; White, Michael K.; Strenge, Dennis L.; Aaberg, Rosanne L.; Andrews, William B.

2000-01-01

Documentation of the methodology used to calculate relative hazard and risk measure results for the DOE complex wide risk profiles. This methodology is used on major site risk profiles. In February 1997, the Center for Risk Excellence (CRE) was created and charged as a technical, field-based partner to the Office of Science and Risk Policy (EM-52). One of the initial charges to the CRE is to assist the sites in the development of ''site risk profiles.'' These profiles are to be relatively short summaries (periodically updated) that present a broad perspective on the major risk related challenges that face the respective site. The risk profiles are intended to serve as a high-level communication tool for interested internal and external parties to enhance the understanding of these risk-related challenges. The risk profiles for each site have been designed to qualitatively present the following information: (1) a brief overview of the site, (2) a brief discussion on the historical mission of the site, (3) a quote from the site manager indicating the site's commitment to risk management, (4) a listing of the site's top risk-related challenges, (5) a brief discussion and detailed table presenting the site's current risk picture, (6) a brief discussion and detailed table presenting the site's future risk reduction picture, and (7) graphic illustrations of the projected management of the relative hazards at the site. The graphic illustrations were included to provide the reader of the risk profiles with a high-level mental picture to associate with all the qualitative information presented in the risk profile. Inclusion of these graphic illustrations presented the CRE with the challenge of how to fold this high-level qualitative risk information into a system to produce a numeric result that would depict the relative change in hazard, associated with each major risk management action, so it could be presented graphically. This report presents the methodology developed

Public relations in risk communication: risk pr. The importance of public relations for risk communication; Public Relations in der Risikokommunikation: Risiko-PR. Die Bedeutung von Public Relations fuer die Risikokommunikation

Energy Technology Data Exchange (ETDEWEB)

Lehmann, K.

2001-07-01

Risks have become a central problem of our time, as is reflected in concepts like 'society at risk' and 'anti-technological attitude', in group protest against risks and against those who cause them, and last but not least in the critical attitude of the media. Against this background, organisations must needs enter the public discussion and be able to communicate professionally and convincingly in order to ensure their own success and further existence. The book describes the basic problems of risk research and risk communications and discusses inhowfar, and how, public relations strategies and instruments can help here. [German] Risiken werden verstaerkt zum Problem unserer Zeit. Das belegen nicht nur Begriffe wie 'Risikogesellschaft' und 'Technikfeindlichkeit', die in letzter Zeit an Bedeutung gewonnen haben, sondern auch und vor allem nachhaltige Proteste von engagierten Gruppierungen gegen Risiken und deren Verursacher oder auch die kritische Berichterstattung der Medien. Vor diesem Hintergrund ist es fuer Organisationen erforderlich, in die oeffentliche Auseinandersetzung um Risiken einzusteigen und hier professionell und ueberzeugend zu kommunizieren, um den Organisationserfolg und Organisationsbestand zu sichern. Die vorliegende Arbeit beschreibt die Grundprobleme der Risikoforschung und Risikokommunikation und diskutiert, ob und inwieweit Public Relations bei der Loesung dieser Probleme helfen koennen, da insbesondere Public Relations gezielt Strategien und Instrumente nutzen, um beispielsweise den Wissensstand der Oeffentlichkeit zu verbessern und den Dialog mit relevanten Teiloeffentlichkeiten zu foerdern. (orig.)

Generation of risk importance information from severe accident PSA model

International Nuclear Information System (INIS)

Seo, Mi Ro; Kim, Hyeong Taek; Moon, Chan Kook

2012-01-01

One of the important objects conducting Probabilistic Safety Assessment (PSA) is the relative evaluation of importance of the component or function that is greatly affected to the plant safety. This evaluation is performed by the importance assessment methods such as Risk Reduction Worth, Risk Achievement Worth, and Fuss el Vessley method from the aspect of core damage frequency (CDF). In the Level 1 PSA model, the importance of each component can be evaluated since the CDF is calculated by the combination of the branch probability of event tree and the component failure probability in the fault tree. But, the Level 2 PSA model in order to assess the containment integrity cannot evaluate the risk importance by the above methods because the model is consisted of 3 parts, plant damage status, containment event tree, and source term category. So, in the field that the Level 2 PSA risk importance information should be reflected, such as maintenance rule program, risk importance has been determined by the subjective judgment of the model developer. This study was performed in order to generate the risk importance information more objectively and systematically in the Level 2 PSA model, focused on the containment event tree in the domain PHWR Level 2 PSA model

Risk of fall-related injury in people with lower limb amputations: A prospective cohort study.

Science.gov (United States)

Wong, Christopher Kevin; Chihuri, Stanford T; Li, Guohua

2016-01-01

To assess fall-related injury risk and risk factors in people with lower limb amputation. Prospective longitudinal cohort with follow-up every 6 months for up to 41 months. Community-dwelling adults with lower limb amputations of any etiology and level recruited from support groups and prosthetic clinics. Demographic and clinical characteristics were obtained by self-reported questionnaire and telephone or in-person follow-up. Fall-related injury incidence requiring medical care per person-month and adjusted hazard ratio of fall-related injury were calculated using multivariable proportional hazards regression modeling. A total of 41 subjects, with 782 follow-up person-months in total, had 11 fall-related injury incidents (14.1/1,000 person-months). During follow-up, 56.1% of subjects reported falling and 26.8% reported fall-related injury. Multivariable proportional hazard modeling showed that women were nearly 6 times more likely as men to experience fall-related injury and people of non-white race were 13 times more likely than people of white race to experience fall-related injury. The final predictive model also included vascular amputation and age. Risk of fall-related injury requiring medical care in people with lower limb amputation appears to be higher than in older adult inpatients. Intervention programs to prevent fall-related injury in people with lower limb amputation should target women and racial minorities.

Why we need new approaches to low-dose risk modeling

International Nuclear Information System (INIS)

Alvarez, J.L.; Seiler, F.A.

1996-01-01

The linear no-threshold model for radiation effects was introduced as a conservative model for the design of radiation protection programs. The model has persisted not only as the basis for such programs, but has come to be treated as a dogma and is often confused with scientific fact. In this examination a number of serious problems with the linear no-threshold model of radiation carcinogenesis were demonstrated, many of them invalidating the hypothesis. It was shown that the relative risk formalism did not approach 1 as the dose approaches zero. When morality ratios were used instead, the data in the region below 0.3 Sv were systematically below the predictions of the linear model. It was also shown that the data above 0.3 Sv were of little use in formulating a model at low doses. In addition, these data are valid only for doses accumulated at high dose rates, and there is no scientific justification for using the model in low-dose, low-dose-rate extrapolations for purposes of radiation protection. Further examination of model fits to the Japanese survivor data were attempted. Several such models were fit to the data including an unconstrained linear, linear-square root, and Weibull, all of which fit the data better than the relative risk, linear no-threshold model. These fits were used to demonstrate that the linear model systematically over estimates the risk at low doses in the Japanese survivor data set. It is recommended here that an unbiased re-analysis of the data be undertaken and the results used to construct a new model, based on all pertinent data. This model could then form the basis for managing radiation risks in the appropriate regions of dose and dose rate

Model based climate information on drought risk in Africa

Science.gov (United States)

Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

2012-04-01

The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

Analysis of risk factors and the establishment of a risk model for peripherally inserted central catheter thrombosis

OpenAIRE

Fang Hu; Ruo-Nan Hao; Jie Zhang; Zhi-Cheng Ma

2016-01-01

Objective: To investigate the main risk factors of peripherally inserted central catheter (PICC) related upper extremity deep venous thrombosis and establish the risk predictive model of PICC-related upper extremity deep venous thrombosis. Methods: Patients with PICC who were hospitalized between January 2014 and July 2015 were studied retrospectively; they were divided into a thrombosis group (n = 52), with patients who had a venous thrombosis complication after PICC, and a no-thrombosis ...

Some statistical considerations related to the estimation of cancer risk following exposure to ionizing radiation

International Nuclear Information System (INIS)

Land, C.E.; Pierce, D.A.

1983-01-01

Statistical theory and methodology provide the logical structure for scientific inference about the cancer risk associated with exposure to ionizing radiation. Although much is known about radiation carcinogenesis, the risk associated with low-level exposures is difficult to assess because it is too small to measure directly. Estimation must therefore depend upon mathematical models which relate observed risks at high exposure levels to risks at lower exposure levels. Extrapolated risk estimates obtained using such models are heavily dependent upon assumptions about the shape of the dose-response relationship, the temporal distribution of risk following exposure, and variation of risk according to variables such as age at exposure, sex, and underlying population cancer rates. Expanded statistical models, which make explicit certain assumed relationships between different data sets, can be used to strengthen inferences by incorporating relevant information from diverse sources. They also allow the uncertainties inherent in information from related data sets to be expressed in estimates which partially depend upon that information. To the extent that informed opinion is based upon a valid assessment of scientific data, the larger context of decision theory, which includes statistical theory, provides a logical framework for the incorporation into public policy decisions of the informational content of expert opinion

Norms and international standards related to reduce risk management: A literature review

Directory of Open Access Journals (Sweden)

César Fuentes

2011-09-01

Full Text Available The current work aims to develop a revision of the literature within the main concepts in the international rules and standards related to risk management in companies. By this way, there will be an analysis of issues such as the COSO - ERM model, an introduction to the ISO 27000 and 31000 standards; and the Project Management according to PMI targeted at risk management

A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

Science.gov (United States)

Clark, Renee M; Besterfield-Sacre, Mary E

2009-03-01

We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

Explanatory risk factors in the relations between schizotypy and indicators of suicide risk.

Science.gov (United States)

Jahn, Danielle R; DeVylder, Jordan E; Hilimire, Matthew R

2016-04-30

Schizotypy has been linked to suicide risk, but it is not known whether established suicide-related risk factors mediate this relation. The aim of this study was to assess the mediating effects of depressive symptoms, social anxiety, self-esteem, and intimate disclosure in peer relationships in the relation between interpersonal schizotypy and suicide ideation or lifetime suicide attempts. This aim was tested in 590 young adults using a nonparametric bootstrapping procedure. After inclusion of the mediators, interpersonal schizotypy was no longer directly associated with either suicide ideation or lifetime suicide attempts. Depression and self-esteem mediated the relation between interpersonal schizotypy and suicide ideation. No variables mediated the relation between interpersonal schizotypy and lifetime suicide attempts, and there were no significant direct relations when mediators were included. Schizotypy appears to be a distal risk factor for suicidal behavior; assessing depressive symptoms and self-esteem may provide more proximal information about suicide risk, and may be targets for mitigating suicide risk in individuals with schizotypy. Published by Elsevier Ireland Ltd.

Integrating health belief model and technology acceptance model: an investigation of health-related internet use.

Science.gov (United States)

Ahadzadeh, Ashraf Sadat; Pahlevan Sharif, Saeed; Ong, Fon Sim; Khong, Kok Wei

2015-02-19

Today, people use the Internet to satisfy health-related information and communication needs. In Malaysia, Internet use for health management has become increasingly significant due to the increase in the incidence of chronic diseases, in particular among urban women and their desire to stay healthy. Past studies adopted the Technology Acceptance Model (TAM) and Health Belief Model (HBM) independently to explain Internet use for health-related purposes. Although both the TAM and HBM have their own merits, independently they lack the ability to explain the cognition and the related mechanism in which individuals use the Internet for health purposes. This study aimed to examine the influence of perceived health risk and health consciousness on health-related Internet use based on the HBM. Drawing on the TAM, it also tested the mediating effects of perceived usefulness of the Internet for health information and attitude toward Internet use for health purposes for the relationship between health-related factors, namely perceived health risk and health consciousness on health-related Internet use. Data obtained for the current study were collected using purposive sampling; the sample consisted of women in Malaysia who had Internet access. The partial least squares structural equation modeling method was used to test the research hypotheses developed. Perceived health risk (β=.135, t1999=2.676) and health consciousness (β=.447, t1999=9.168) had a positive influence on health-related Internet use. Moreover, perceived usefulness of the Internet and attitude toward Internet use for health-related purposes partially mediated the influence of health consciousness on health-related Internet use (β=.025, t1999=3.234), whereas the effect of perceived health risk on health-related Internet use was fully mediated by perceived usefulness of the Internet and attitude (β=.029, t1999=3.609). These results suggest the central role of perceived usefulness of the Internet and

Korean risk assessment model for breast cancer risk prediction.

Science.gov (United States)

Park, Boyoung; Ma, Seung Hyun; Shin, Aesun; Chang, Myung-Chul; Choi, Ji-Yeob; Kim, Sungwan; Han, Wonshik; Noh, Dong-Young; Ahn, Sei-Hyun; Kang, Daehee; Yoo, Keun-Young; Park, Sue K

2013-01-01

We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort. The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (pKorean women, especially urban women.

Risk related behaviour under different ambient scent conditions

Directory of Open Access Journals (Sweden)

Alina Gagarina

2016-09-01

Full Text Available The article analyses the effect of two ambient scents (peppermint and vanilla and their intensiveness on risk related behaviour that is expressed through selected decision making heuristics. Purpose of the article: The purpose of this article is to identify the relationship of ambient scent type and intensiveness with risk related behaviour that is expressed through selected decision making heuristics. Methodology/methods: 2×2 factorial experiment with control group was run. Ambient scent type (vanilla vs. peppermint and intensiveness (8 (1mg vs. 16 sprays (2mg of scent concentrate in the same room were manipulated as between subject variables. Risk aversion, effect of anchoring heuristic on bidding, and affect (risk and benefit heuristics were tracked as dependent variables. Scientific aim: To identify whether ambient scent type and intensiveness have effect on risk related behaviour. Findings: Evidence suggests that there are effects of ambient scent on risk related behaviour, thus fulfilling the missing gap to relate ambient environment to decision making heuristics when risks are involved. However, not all heuristics were affected by experimental conditions. Subjects were bidding significantly higher amounts under low anchor conditions, when peppermint scent was around (if compared to vanilla group. Affect risk was perceived as lower in peppermint ambient scent conditions, if compared to the control group. Intensity of ambient scent also had influence on affect risk: subjects perceived less risk under high scent intensity conditions. Conclusions: By manipulating ambient scent, marketers may reduce or increase consumers risk perception and behaviour and as a consequence influence their purchase decisions. Marketers could use peppermint scent in high intensiveness in the situations where they want consumers to undertake higher risks (expensive purchases, gambling, insurance, since stakes were higher under peppermint ambient scent condition

Model of MSD Risk Assessment at Workplace

OpenAIRE

K. Sekulová; M. Šimon

2015-01-01

This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

Lung cancer risk in relation to traffic-related nano/ultrafine particle-bound PAHs exposure: a preliminary probabilistic assessment.

Science.gov (United States)

Liao, Chung-Min; Chio, Chia-Pin; Chen, Wei-Yu; Ju, Yun-Ru; Li, Wen-Hsuan; Cheng, Yi-Hsien; Liao, Vivian Hsiu-Chuan; Chen, Szu-Chieh; Ling, Min-Pei

2011-06-15

Exposures to carcinogenic polycyclic aromatic hydrocarbons (PAHs) have been linked to human lung cancer. The purpose of this study was to assess lung cancer risk caused by inhalation exposure to nano/ultrafine particle-bound PAHs at the population level in Taiwan appraised with recent published data. A human respiratory tract model was linked with a physiologically based pharmacokinetic model to estimate deposition fraction and internal organic-specific PAHs doses. A probabilistic risk assessment framework was developed to estimate potential lung cancer risk. We reanalyzed particle size distribution, total-PAHs, particle-bound benzo(a)pyrene (B[a]P) and PM concentrations. A dose-response profile describing the relationships between external B[a]P concentration and lung cancer risk response was constructed based on population attributable fraction (PAF). We found that 90% probability lung cancer risks ranged from 10(-5) to 10(-4) for traffic-related nano and ultrafine particle-bound PAHs, indicating a potential lung cancer risk. The particle size-specific PAF-based excess annual lung cancer incidence rate due to PAHs exposure was estimated to be less than 1 per 100,000 population, indicating a mild risk factor for lung cancer. We concluded that probabilistic risk assessment linked PAF for limiting cumulative PAHs emissions to reduce lung cancer risk plays a prominent role in future government risk assessment program. Copyright © 2011 Elsevier B.V. All rights reserved.

East meets West: the influence of racial, ethnic and cultural risk factors on cardiac surgical risk model performance.

Science.gov (United States)

Soo-Hoo, Sarah; Nemeth, Samantha; Baser, Onur; Argenziano, Michael; Kurlansky, Paul

2018-01-01

To explore the impact of racial and ethnic diversity on the performance of cardiac surgical risk models, the Chinese SinoSCORE was compared with the Society of Thoracic Surgeons (STS) risk model in a diverse American population. The SinoSCORE risk model was applied to 13 969 consecutive coronary artery bypass surgery patients from twelve American institutions. SinoSCORE risk factors were entered into a logistic regression to create a 'derived' SinoSCORE whose performance was compared with that of the STS risk model. Observed mortality was 1.51% (66% of that predicted by STS model). The SinoSCORE 'low-risk' group had a mortality of 0.15%±0.04%, while the medium-risk and high-risk groups had mortalities of 0.35%±0.06% and 2.13%±0.14%, respectively. The derived SinoSCORE model had a relatively good discrimination (area under of the curve (AUC)=0.785) compared with that of the STS risk score (AUC=0.811; P=0.18 comparing the two). However, specific factors that were significant in the original SinoSCORE but that lacked significance in our derived model included body mass index, preoperative atrial fibrillation and chronic obstructive pulmonary disease. SinoSCORE demonstrated limited discrimination when applied to an American population. The derived SinoSCORE had a discrimination comparable with that of the STS, suggesting underlying similarities of physiological substrate undergoing surgery. However, differential influence of various risk factors suggests that there may be varying degrees of importance and interactions between risk factors. Clinicians should exercise caution when applying risk models across varying populations due to potential differences that racial, ethnic and geographic factors may play in cardiac disease and surgical outcomes.

Analysis of uncertainty in modeling perceived risks

International Nuclear Information System (INIS)

Melnyk, R.; Sandquist, G.M.

2005-01-01

Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

Relative and absolute risk in epidemiology and health physics

International Nuclear Information System (INIS)

Goldsmith, R.; Peterson, H.T. Jr.

1983-01-01

The health risk from ionizing radiation commonly is expressed in two forms: (1) the relative risk, which is the percentage increase in natural disease rate and (2) the absolute or attributable risk which represents the difference between the natural rate and the rate associated with the agent in question. Relative risk estimates for ionizing radiation generally are higher than those expressed as the absolute risk. This raises the question of which risk estimator is the most appropriate under different conditions. The absolute risk has generally been used for radiation risk assessment, although mathematical combinations such as the arithmetic or geometric mean of both the absolute and relative risks, have also been used. Combinations of the two risk estimators are not valid because the absolute and relative risk are not independent variables. Both human epidemiologic studies and animal experimental data can be found to illustrate the functional relationship between the natural cancer risk and the risk associated with radiation. This implies that the radiation risk estimate derived from one population may not be appropriate for predictions in another population, unless it is adjusted for the difference in the natural disease incidence between the two populations

Dealing with project complexity by matrix-based propagation modelling for project risk analysis

OpenAIRE

Fang , Chao; Marle , Franck

2012-01-01

International audience; Engineering projects are facing a growing complexity and are thus exposed to numerous and interdependent risks. In this paper, we present a quantitative method for modelling propagation behaviour in the project risk network. The construction of the network requires the involvement of the project manager and related experts using the Design Structure Matrix (DSM) method. A matrix-based risk propagation model is introduced to calculate risk propagation and thus to re-eva...

Risk modelling in portfolio optimization

Science.gov (United States)

Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-09-01

Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

Science.gov (United States)

Doroszkiewicz, J. M.; Romanowicz, R. J.

2016-12-01

The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the

Pregnancy-related venous thromboembolism and risk of occult cancer

DEFF Research Database (Denmark)

Tarp Hansen, Anette; Veres, Katalin; Horváth-Puhó, Erzsébet

2017-01-01

The cancer risk during the first year after a pregnancy-related venous thromboembolism episode is higher than expected.An aggressive search for cancer in women with pregnancy-related venous thromboembolism is probably not warranted, due to low absolute risk.......The cancer risk during the first year after a pregnancy-related venous thromboembolism episode is higher than expected.An aggressive search for cancer in women with pregnancy-related venous thromboembolism is probably not warranted, due to low absolute risk....

Pregnancy-related venous thromboembolism and risk of occult cancer

DEFF Research Database (Denmark)

Hansen, Anette Tarp; Veres, Katalin; Horváth-Puhó, Erzsébet

2017-01-01

The cancer risk during the first year after a pregnancy-related venous thromboembolism episode is higher than expected. An aggressive search for cancer in women with pregnancy-related venous thromboembolism is probably not warranted, due to low absolute risk.......The cancer risk during the first year after a pregnancy-related venous thromboembolism episode is higher than expected. An aggressive search for cancer in women with pregnancy-related venous thromboembolism is probably not warranted, due to low absolute risk....

Strategy for prioritizing whistleblowing with potential risks related to health services

Directory of Open Access Journals (Sweden)

Rafael Fernandes Barros

2017-11-01

Full Text Available Introduction: The Sanitary Surveillance of Health Services receives daily denunciations that refer to situations of risk that can hardly be measured quantitatively and attribute to some type of specific damage, in a context of great uncertainty. Objective: Considering such situations should be adequately addressed under the health risk paradigm, this work had as objective identifying notions about risk and its forms of analysis in the scope of Sanitary Surveillance of Health Services, as well as the existence of strategies and models in the analysis and treatment of denunciations. Method: An extensive literature review (through the Regional Portal of the BVS, databases SciELO and SciELO Books, and the journal Visa em Debate was conducted. Results: Although the results point to a relatively recent discussion regarding the model of potential risk analysis as an operational concept for the field of health surveillance in health services, there is no description of strategies or models applied to the analysis or treatment of whistleblowing. Thus, it is discussed and proposed a strategy for the initial analysis of reports with potential risk, which seeks to bring minimally objective criteria, in a field marked by enormous subjectivity. Conclusions: We conclude by indicating that the presented strategy is an initial instrument for the management of whistleblowing that must be discussed and adapted to the reality and context of health surveillance agencies.

Conceptualizing a Dynamic Fall Risk Model Including Intrinsic Risks and Exposures.

Science.gov (United States)

Klenk, Jochen; Becker, Clemens; Palumbo, Pierpaolo; Schwickert, Lars; Rapp, Kilan; Helbostad, Jorunn L; Todd, Chris; Lord, Stephen R; Kerse, Ngaire

2017-11-01

Falls are a major cause of injury and disability in older people, leading to serious health and social consequences including fractures, poor quality of life, loss of independence, and institutionalization. To design and provide adequate prevention measures, accurate understanding and identification of person's individual fall risk is important. However, to date, the performance of fall risk models is weak compared with models estimating, for example, cardiovascular risk. This deficiency may result from 2 factors. First, current models consider risk factors to be stable for each person and not change over time, an assumption that does not reflect real-life experience. Second, current models do not consider the interplay of individual exposure including type of activity (eg, walking, undertaking transfers) and environmental risks (eg, lighting, floor conditions) in which activity is performed. Therefore, we posit a dynamic fall risk model consisting of intrinsic risk factors that vary over time and exposure (activity in context). eHealth sensor technology (eg, smartphones) begins to enable the continuous measurement of both the above factors. We illustrate our model with examples of real-world falls from the FARSEEING database. This dynamic framework for fall risk adds important aspects that may improve understanding of fall mechanisms, fall risk models, and the development of fall prevention interventions. Copyright © 2017 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Modeling the Risk of Secondary Malignancies after Radiotherapy

Directory of Open Access Journals (Sweden)

Uwe Schneider

2011-11-01

Full Text Available In developed countries, more than half of all cancer patients receive radiotherapy at some stage in the management of their disease. However, a radiation-induced secondary malignancy can be the price of success if the primary cancer is cured or at least controlled. Therefore, there is increasing concern regarding radiation-related second cancer risks in long-term radiotherapy survivors and a corresponding need to be able to predict cancer risks at high radiation doses. Of particular interest are second cancer risk estimates for new radiation treatment modalities such as intensity modulated radiotherapy, intensity modulated arc-therapy, proton and heavy ion radiotherapy. The long term risks from such modern radiotherapy treatment techniques have not yet been determined and are unlikely to become apparent for many years, due to the long latency time for solid tumor induction. Most information on the dose-response of radiation-induced cancer is derived from data on the A-bomb survivors who were exposed to γ-rays and neutrons. Since, for radiation protection purposes, the dose span of main interest is between zero and one Gy, the analysis of the A-bomb survivors is usually focused on this range. With increasing cure rates, estimates of cancer risk for doses larger than one Gy are becoming more important for radiotherapy patients. Therefore in this review, emphasis was placed on doses relevant for radiotherapy with respect to radiation induced solid cancer. Simple radiation protection models should be used only with extreme care for risk estimates in radiotherapy, since they are developed exclusively for low dose. When applied to scatter radiation, such models can predict only a fraction of observed second malignancies. Better semi-empirical models include the effect of dose fractionation and represent the dose-response relationships more accurately. The involved uncertainties are still huge for most of the organs and tissues. A major reason for

Risk factors for work-related eczema and urticaria among vocational students of agriculture.

Science.gov (United States)

Śpiewak, Radosław; Góra-Florek, Anna; Horoch, Andrzej; Jarosz, Mirosław J; Doryńska, Agnieszka; Golec, Marcin; Dutkiewicz, Jacek

2017-12-23

Farmers are at high risk of occupational skin diseases which may start already during vocational training. This study was aimed at identification of risk factors for work-related skin diseases among vocational students of agriculture. The study involved 440 students (245 males, 195 females aged 17-21 years) in 11 vocational schools which were at least 100 km from each other. The protocol included a physician-managed questionnaire and medical examination, skin prick tests, patch tests, total IgE and Phadiatop. Logistic regression model was used for the identification of relevant risk factors. Work-related dermatoses were diagnosed in 29 study participants (6.6%, 95%CI: 4.3-8.9%): eczema in 22, urticaria in 14, and co-existence of both in 7 students. Significant risk factors for work-related eczema were: history of respiratory allergy (OR=10.10; pagriculture. Atopy, past history of asthma, allergic rhinitis, and eczema (either atopic, allergic or irritant) are relevant risk factors for work-related eczema and urticaria in young farmers, along with family history of any skin disease. Positive skin prick tests seem relevant, especially in the case of urticaria. Asking simple, aimed questions during health checks while enrolling students into agricultural schools would suffice to identify students at risk for work-related eczema and urticaria, giving them the chance for selecting a safer profession, and hopefully avoiding an occupational disease in the future.

Treatment-dependent and treatment-independent risk factors associated with the risk of diabetes-related events

DEFF Research Database (Denmark)

Wilke, Thomas; Mueller, Sabrina; Groth, Antje

2015-01-01

BACKGROUND: The aim of this study was to analyse which factors predict the real-world macro-/microvascular event, hospitalisation and death risk in patients with type 2 diabetes mellitus. Furthermore, we aimed to investigate whether there exists both an under- and over-treatment risk...... of these patients. METHODS: We used a German claims/clinical data set covering the years 2010-12. Diabetes-related events were defined as (1) macro-, (2) microvascular events leading to inpatient hospitalisation, (3) other hospitalisations with type 2 diabetes mellitus as main diagnosis, (4) all-cause death and (5......) a composite outcome including all event categories 1-4. Factors associated with event risk were analysed by a Kaplan-Meier curve analysis and by multivariable Cox regression models. RESULTS: 229,042 patients with type 2 diabetes mellitus (mean age 70.2 years; mean CCI 6.03) were included. Among factors...

Environmental modeling and health risk analysis (ACTS/RISK)

National Research Council Canada - National Science Library

Aral, M. M

2010-01-01

... presents a review of the topics of exposure and health risk analysis. The Analytical Contaminant Transport Analysis System (ACTS) and Health RISK Analysis (RISK) software tools are an integral part of the book and provide computational platforms for all the models discussed herein. The most recent versions of these two softwa...

A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model.

Science.gov (United States)

Harrison, David A; Parry, Gareth J; Carpenter, James R; Short, Alasdair; Rowan, Kathy

2007-04-01

To develop a new model to improve risk prediction for admissions to adult critical care units in the UK. Prospective cohort study. The setting was 163 adult, general critical care units in England, Wales, and Northern Ireland, December 1995 to August 2003. Patients were 216,626 critical care admissions. None. The performance of different approaches to modeling physiologic measurements was evaluated, and the best methods were selected to produce a new physiology score. This physiology score was combined with other information relating to the critical care admission-age, diagnostic category, source of admission, and cardiopulmonary resuscitation before admission-to develop a risk prediction model. Modeling interactions between diagnostic category and physiology score enabled the inclusion of groups of admissions that are frequently excluded from risk prediction models. The new model showed good discrimination (mean c index 0.870) and fit (mean Shapiro's R 0.665, mean Brier's score 0.132) in 200 repeated validation samples and performed well when compared with recalibrated versions of existing published risk prediction models in the cohort of patients eligible for all models. The hypothesis of perfect fit was rejected for all models, including the Intensive Care National Audit & Research Centre (ICNARC) model, as is to be expected in such a large cohort. The ICNARC model demonstrated better discrimination and overall fit than existing risk prediction models, even following recalibration of these models. We recommend it be used to replace previously published models for risk adjustment in the UK.

Estimation of Employee Turnover with Competing Risks Models

Directory of Open Access Journals (Sweden)

Grzenda Wioletta

2015-12-01

Full Text Available Employee turnover accompanies every business organization, regardless of the industry and size. Nowadays, many companies struggle with problems related to the lack of sufficient information about the nature of employee turnover processes. Therefore, comprehensive analysis of these processes is necessary. This article aims to examine the turnover of employees from a big manufacturing company using competing risks models with covariates and without covariates. This technique allows to incorporate the information about the type of employment contract termination. Moreover, Cox proportional hazard model enables the researcher to analyse simultaneously multiple factors that affect employment duration. One of the major observations is that employee remuneration level differentiates most strongly the risk of job resignation.

Methodological issues in cardiovascular epidemiology: the risk of determining absolute risk through statistical models

Directory of Open Access Journals (Sweden)

Demosthenes B Panagiotakos

2006-09-01

Full Text Available Demosthenes B Panagiotakos, Vassilis StavrinosOffice of Biostatistics, Epidemiology, Department of Dietetics, Nutrition, Harokopio University, Athens, GreeceAbstract: During the past years there has been increasing interest in the development of cardiovascular disease functions that predict future events at individual level. However, this effort has not been so far very successful, since several investigators have reported large differences in the estimation of the absolute risk among different populations. For example, it seems that predictive models that have been derived from US or north European populations  overestimate the incidence of cardiovascular events in south European and Japanese populations. A potential explanation could be attributed to several factors such as geographical, cultural, social, behavioral, as well as genetic variations between the investigated populations in addition to various methodological, statistical, issues relating to the estimation of these predictive models. Based on current literature it can be concluded that, while risk prediction of future cardiovascular events is a useful tool and might be valuable in controlling the burden of the disease in a population, further work is required to improve the accuracy of the present predictive models.Keywords: cardiovascular disease, risk, models

Additive gamma frailty models with applications to competing risks in related individuals

DEFF Research Database (Denmark)

Eriksson, Frank; Scheike, Thomas

2015-01-01

Epidemiological studies of related individuals are often complicated by the fact that follow-up on the event type of interest is incomplete due to the occurrence of other events. We suggest a class of frailty models with cause-specific hazards for correlated competing events in related individual...

Chronic Stress Decreases Basal Levels of Memory-Related Signaling Molecules in Area CA1 of At-Risk (Subclinical) Model of Alzheimer's Disease.

Science.gov (United States)

Alkadhi, Karim A; Tran, Trinh T

2015-08-01

An important factor that may affect the severity and time of onset of Alzheimer's disease (AD) is chronic stress. Epidemiological studies report that chronically stressed individuals are at an increased risk for developing AD. The purpose of this study was to reveal whether chronic psychosocial stress could hasten the appearance of AD symptoms including changes in basal levels of cognition-related signaling molecules in subjects who are at risk for the disease. We investigated the effect of chronic psychosocial stress on basal levels of memory-related signaling molecules in area CA1 of subclinical rat model of AD. The subclinical symptomless rat model of AD was induced by osmotic pump continuous intracerebroventricular (ICV) infusion of 160 pmol/day Aβ1-42 for 14 days. Rats were chronically stressed using the psychosocial stress intruder model. Western blot analysis of basal protein levels of important signaling molecules in hippocampal area CA1 showed no significant difference between the subclinical AD rat model and control rat. Following six weeks of psychosocial stress, molecular analysis showed that subclinical animals subjected to stress have significantly reduced basal levels of p-CaMKII and decreased p-CaMKII/t-CaMKII ratio as well as decreased basal levels of p-CREB, total CREB, and BDNF. The present results suggest that these changes in basal levels of signaling molecules may be responsible for impaired learning, memory, and LTP in this rat model, which support the proposition that chronic stress may accelerate the emergence of AD in susceptible individuals.

Causation in risk assessment and management: models, inference, biases, and a microbial risk-benefit case study.

Science.gov (United States)

Cox, L A; Ricci, P F

2005-04-01

Causal inference of exposure-response relations from data is a challenging aspect of risk assessment with important implications for public and private risk management. Such inference, which is fundamentally empirical and based on exposure (or dose)-response models, seldom arises from a single set of data; rather, it requires integrating heterogeneous information from diverse sources and disciplines including epidemiology, toxicology, and cell and molecular biology. The causal aspects we discuss focus on these three aspects: drawing sound inferences about causal relations from one or more observational studies; addressing and resolving biases that can affect a single multivariate empirical exposure-response study; and applying the results from these considerations to the microbiological risk management of human health risks and benefits of a ban on antibiotic use in animals, in the context of banning enrofloxacin or macrolides, antibiotics used against bacterial illnesses in poultry, and the effects of such bans on changing the risk of human food-borne campylobacteriosis infections. The purposes of this paper are to describe novel causal methods for assessing empirical causation and inference; exemplify how to deal with biases that routinely arise in multivariate exposure- or dose-response modeling; and provide a simplified discussion of a case study of causal inference using microbial risk analysis as an example. The case study supports the conclusion that the human health benefits from a ban are unlikely to be greater than the excess human health risks that it could create, even when accounting for uncertainty. We conclude that quantitative causal analysis of risks is a preferable to qualitative assessments because it does not involve unjustified loss of information and is sound under the inferential use of risk results by management.

Ruin Probabilities in a Dependent Discrete-Time Risk Model With Gamma-Like Tailed Insurance Risks

Directory of Open Access Journals (Sweden)

Xing-Fang Huang

2017-03-01

Full Text Available This paper considered a dependent discrete-time risk model, in which the insurance risks are represented by a sequence of independent and identically distributed real-valued random variables with a common Gamma-like tailed distribution; the financial risks are denoted by another sequence of independent and identically distributed positive random variables with a finite upper endpoint, but a general dependence structure exists between each pair of the insurance risks and the financial risks. Following the works of Yang and Yuen in 2016, we derive some asymptotic relations for the finite-time and infinite-time ruin probabilities. As a complement, we demonstrate our obtained result through a Crude Monte Carlo (CMC simulation with asymptotics.

Risk Estimation for Lung Cancer in Libya: Analysis Based on Standardized Morbidity Ratio, Poisson-Gamma Model, BYM Model and Mixture Model

Science.gov (United States)

Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

2017-03-01

Cancer is the most rapidly spreading disease in the world, especially in developing countries, including Libya. Cancer represents a significant burden on patients, families, and their societies. This disease can be controlled if detected early. Therefore, disease mapping has recently become an important method in the fields of public health research and disease epidemiology. The correct choice of statistical model is a very important step to producing a good map of a disease. Libya was selected to perform this work and to examine its geographical variation in the incidence of lung cancer. The objective of this paper is to estimate the relative risk for lung cancer. Four statistical models to estimate the relative risk for lung cancer and population censuses of the study area for the time period 2006 to 2011 were used in this work. They are initially known as Standardized Morbidity Ratio, which is the most popular statistic, which used in the field of disease mapping, Poisson-gamma model, which is one of the earliest applications of Bayesian methodology, Besag, York and Mollie (BYM) model and Mixture model. As an initial step, this study begins by providing a review of all proposed models, which we then apply to lung cancer data in Libya. Maps, tables and graph, goodness-of-fit (GOF) were used to compare and present the preliminary results. This GOF is common in statistical modelling to compare fitted models. The main general results presented in this study show that the Poisson-gamma model, BYM model, and Mixture model can overcome the problem of the first model (SMR) when there is no observed lung cancer case in certain districts. Results show that the Mixture model is most robust and provides better relative risk estimates across a range of models. Creative Commons Attribution License

Quantifying risk over the life course - latency, age-related susceptibility, and other time-varying exposure metrics.

Science.gov (United States)

Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna

2016-06-15

Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional, and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses' Health Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Models of Credit Risk Measurement

OpenAIRE

Hagiu Alina

2011-01-01

Credit risk is defined as that risk of financial loss caused by failure by the counterparty. According to statistics, for financial institutions, credit risk is much important than market risk, reduced diversification of the credit risk is the main cause of bank failures. Just recently, the banking industry began to measure credit risk in the context of a portfolio along with the development of risk management started with models value at risk (VAR). Once measured, credit risk can be diversif...

Models for assessing and managing credit risk

Directory of Open Access Journals (Sweden)

Neogradi Slađana

2014-01-01

Full Text Available This essay deals with the definition of a model for assessing and managing credit risk. Risk is an inseparable component of any average and normal credit transaction. Looking at the different aspects of the identification and classification of risk in the banking industry as well as representation of the key components of modern risk management. In the first part of the essay will analyze how the impact of credit risk on bank and empirical models for determining the financial difficulties in which the company can be found. Bank on the basis of these models can reduce number of approved risk assets. In the second part, we consider models for improving credit risk with emphasis on Basel I, II and III, and the third part, we conclude that the most appropriate model and gives the best effect for measuring credit risk in domestic banks.

Revenue Risk Modelling and Assessment on BOT Highway Project

Science.gov (United States)

Novianti, T.; Setyawan, H. Y.

2018-01-01

The infrastructure project which is considered as a public-private partnership approach under BOT (Build-Operate-Transfer) arrangement, such as a highway, is risky. Therefore, assessment on risk factors is essential as the project have a concession period and is influenced by macroeconomic factors and consensus period. In this study, pre-construction risks of a highway were examined by using a Delphi method to create a space for offline expert discussions; a fault tree analysis to map intuition of experts and to create a model from the underlying risk events; a fuzzy logic to interpret the linguistic data of risk models. The loss of revenue for risk tariff, traffic volume, force majeure, and income were then measured. The results showed that the loss of revenue caused by the risk tariff was 10.5% of the normal total revenue. The loss of revenue caused by the risk of traffic volume was 21.0% of total revenue. The loss of revenue caused by the force majeure was 12.2% of the normal income. The loss of income caused by the non-revenue events was 6.9% of the normal revenue. It was also found that the volume of traffic was the major risk of a highway project because it related to customer preferences.

Assessing the risk of work-related international travel.

Science.gov (United States)

Druckman, Myles; Harber, Philip; Liu, Yihang; Quigley, Robert L

2014-11-01

To identify factors affecting the likelihood of requiring medical services during international business trips. Data from more than 800,000 international trips and medical assistance cases provided to 48 multinational corporations in 2009. Travel destination countries were grouped into four a priori risk-related categories. Travel to "low" medical risk countries in aggregate accounted for more hospitalizations and medical evacuations than travel to "high" medical risk countries. Nevertheless, the risk per trip was much higher for travel to higher medical risk countries. Corporations with employees on international travel should allocate sufficient resources to manage and ideally prevent medical issues during business travel. Travel medicine must focus on more than infectious diseases, and programs are necessary for both high- and low-risk regions. Improved understanding of travel-related needs determines resource allocation and risk mitigation efforts.

Chronic and Acute Relational Risk Factors for Dating Aggression in Adolescence and Young Adulthood.

Science.gov (United States)

Collibee, Charlene; Furman, Wyndol

2016-04-01

Dating aggression is a prevalent and costly public health concern. Using a relational risk framework, this study examined acute and chronic relational risk factors (negative interactions, jealousy, support, and relationship satisfaction) and their effects on physical and psychological dating aggression. The study also examined the interaction between chronic and acute risk, allowing us to assess how changes in acute risk have differing effects depending on whether the individual is typically at higher chronic risk. A sample of 200 youth (100 female) completed seven waves of data, which spanned 9 years from middle adolescence to young adulthood (M age at Wave 1 = 15.83). Using hierarchical linear modeling, analyses revealed both acute (within-person) and chronic (between-person) levels in jealousy, negative interactions, and relationship satisfaction, were associated with physical and psychological dating aggression. Significant interactions between chronic and acute risk emerged in predicting physical aggression for negative interactions, jealousy, and relationship satisfaction such that those with higher levels of chronic risk are more vulnerable to increases in acute risk. These interactions between chronic and acute risk indicate that risk is not static, and dating aggression is particularly likely to occur at certain times for youth at high risk for dating aggression. Such periods of increased risk may provide opportunities for interventions to be particularly effective in preventing dating aggression or its consequences. Taken together, these findings provide support for the role of relational risk factors for dating aggression. They also underscore the importance of considering risk dynamically.

Multilevel joint competing risk models

Science.gov (United States)

Karunarathna, G. H. S.; Sooriyarachchi, M. R.

2017-09-01

Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

Combining engineering and data-driven approaches: Development of a generic fire risk model facilitating calibration

DEFF Research Database (Denmark)

De Sanctis, G.; Fischer, K.; Kohler, J.

2014-01-01

Fire risk models support decision making for engineering problems under the consistent consideration of the associated uncertainties. Empirical approaches can be used for cost-benefit studies when enough data about the decision problem are available. But often the empirical approaches...... a generic risk model that is calibrated to observed fire loss data. Generic risk models assess the risk of buildings based on specific risk indicators and support risk assessment at a portfolio level. After an introduction to the principles of generic risk assessment, the focus of the present paper...... are not detailed enough. Engineering risk models, on the other hand, may be detailed but typically involve assumptions that may result in a biased risk assessment and make a cost-benefit study problematic. In two related papers it is shown how engineering and data-driven modeling can be combined by developing...

Evaluation of air pollution-related risks for Austrian mountain forests

International Nuclear Information System (INIS)

Smidt, Stefan; Herman, Friedl

2004-01-01

The present paper describes air pollution status and evaluation of risks related to effects of phytotoxic pollutants in the Austrian mountain forests. The results are based on Austrian networks (Forest Inventory, Forest Damage Monitoring System, Austrian Bioindicator Grid), the Austrian sample plots of the European networks of the UN-ECE (ICP Forests, Level I and Level II) and interdisciplinary research approaches. Based on the monitoring data and on modelling and mapping of Critical Thresholds, the evaluation of risk factors was possible. Cause-effect relationships between air pollution and tree responses were shown by tree-physiological measurements. Sulfur impact, proton and lead input, concentrations of nitrogen oxides, nitrogen input and ozone were evaluated. The risk was demonstrated at a regional and large-scale national level. Especially the increasing O 3 level and the accumulation of Pb with altitude present most serious risk for mountain forests. - Despite strong reduction of emissions in Europe, pollutants are still a potential stress factor, especially for sensitive mountain forest ecosystems in Austria

The care of Filipino juvenile offenders in residential facilities evaluated using the risk-need-responsivity model

NARCIS (Netherlands)

Spruit, A.; Wissink, I.B.; Stams, G.J.J.M.

According to the risk-need-responsivity model of offender, assessment and rehabilitation treatment should target specific factors that are related to re-offending. This study evaluates the residential care of Filipino juvenile offenders using the risk-need-responsivity model. Risk analyses and

People at High Risk of Developing Flu-Related Complications

Science.gov (United States)

... Influenza Types Seasonal Avian Swine Variant Pandemic Other People at High Risk of Developing Flu–Related Complications ... related complications if they get sick with influenza. People at High Risk for Developing Flu-Related Complications ...

A mathematical model for environmental risk assessment in manufacturing industry

Institute of Scientific and Technical Information of China (English)

何莉萍; 徐盛明; 陈大川; 党创寅

2002-01-01

Environmental conscious manufacturing has become an important issue in industry because of market pressure and environmental regulations. An environmental risk assessment model was developed based on the network analytic method and fuzzy set theory. The "interval analysis method" was applied to deal with the on-site monitoring data as basic information for assessment. In addition, the fuzzy set theory was employed to allow uncertain, interactive and dynamic information to be effectively incorporated into the environmental risk assessment. This model is a simple, practical and effective tool for evaluating the environmental risk of manufacturing industry and for analyzing the relative impacts of emission wastes, which are hazardous to both human and ecosystem health. Furthermore, the model is considered useful for design engineers and decision-maker to design and select processes when the costs, environmental impacts and performances of a product are taken into consideration.

Water security, risk, and economic growth: Insights from a dynamical systems model

Science.gov (United States)

Dadson, Simon; Hall, Jim W.; Garrick, Dustin; Sadoff, Claudia; Grey, David; Whittington, Dale

2017-08-01

Investments in the physical infrastructure, human capital, and institutions needed for water resources management have been noteworthy in the development of most civilizations. These investments affect the economy in two distinct ways: (i) by improving the factor productivity of water in multiple economic sectors, especially those that are water intensive such as agriculture and energy and (ii) by reducing acute and chronic harmful effects of water-related hazards like floods, droughts, and water-related diseases. The need for capital investment to mitigate risks and promote economic growth is widely acknowledged, but prior conceptual work on the relationship between water-related investments and economic growth has focused on the productive and harmful roles of water in the economy independently. Here the two influences are combined using a simple, dynamical systems model of water-related investment, risk, and growth. In cases where initial water security is low, initial investment in water-related assets enables growth. Without such investment, losses due to water-related hazards exert a drag on economic growth and may create a poverty trap. The presence and location of the poverty trap is context-specific and depends on the exposure of productive water-related assets to water-related risk. Exogenous changes in water-related risk can potentially push an economy away from a growth path toward a poverty trap. Our investigation shows that an inverted-U-shaped investment relation between the level of investment in water security and the current level of water security leads to faster rates of growth than the alternatives that we consider here, and that this relation is responsible for the "S"-curve that is posited in the literature. These results illustrate the importance of accounting for environmental and health risks in economic models and offer insights for the design of robust policies for investment in water-related productive assets to manage risk, in the face

Assessment of credit risk based on fuzzy relations

Science.gov (United States)

Tsabadze, Teimuraz

2017-06-01

The purpose of this paper is to develop a new approach for an assessment of the credit risk to corporate borrowers. There are different models for borrowers' risk assessment. These models are divided into two groups: statistical and theoretical. When assessing the credit risk for corporate borrowers, statistical model is unacceptable due to the lack of sufficiently large history of defaults. At the same time, we cannot use some theoretical models due to the lack of stock exchange. In those cases, when studying a particular borrower given that statistical base does not exist, the decision-making process is always of expert nature. The paper describes a new approach that may be used in group decision-making. An example of the application of the proposed approach is given.

Melanoma Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Development of a cyber security risk model using Bayesian networks

International Nuclear Information System (INIS)

Shin, Jinsoo; Son, Hanseong; Khalil ur, Rahman; Heo, Gyunyoung

2015-01-01

Cyber security is an emerging safety issue in the nuclear industry, especially in the instrumentation and control (I and C) field. To address the cyber security issue systematically, a model that can be used for cyber security evaluation is required. In this work, a cyber security risk model based on a Bayesian network is suggested for evaluating cyber security for nuclear facilities in an integrated manner. The suggested model enables the evaluation of both the procedural and technical aspects of cyber security, which are related to compliance with regulatory guides and system architectures, respectively. The activity-quality analysis model was developed to evaluate how well people and/or organizations comply with the regulatory guidance associated with cyber security. The architecture analysis model was created to evaluate vulnerabilities and mitigation measures with respect to their effect on cyber security. The two models are integrated into a single model, which is called the cyber security risk model, so that cyber security can be evaluated from procedural and technical viewpoints at the same time. The model was applied to evaluate the cyber security risk of the reactor protection system (RPS) of a research reactor and to demonstrate its usefulness and feasibility. - Highlights: • We developed the cyber security risk model can be find the weak point of cyber security integrated two cyber analysis models by using Bayesian Network. • One is the activity-quality model signifies how people and/or organization comply with the cyber security regulatory guide. • Other is the architecture model represents the probability of cyber-attack on RPS architecture. • The cyber security risk model can provide evidence that is able to determine the key element for cyber security for RPS of a research reactor

Using competing risks model and competing events in outcome of pulmonary tuberculosis patients

Directory of Open Access Journals (Sweden)

Mehdi Kazempour Dizaji

2016-01-01

Conclusions: Use of competing risks model with competing events can provide a better way to understand the associated risk factors co-related with outcome of the pulmonary TB process, especially among DR-TB patients.

Quantifying Risk Over the Life Course – Latency, Age-Related Susceptibility, and Other Time-Varying Exposure Metrics

Science.gov (United States)

Wang, Molin; Liao, Xiaomei; Laden, Francine; Spiegelman, Donna

2016-01-01

Identification of the latency period and age-related susceptibility, if any, is an important aspect of assessing risks of environmental, nutritional and occupational exposures. We consider estimation and inference for latency and age-related susceptibility in relative risk and excess risk models. We focus on likelihood-based methods for point and interval estimation of the latency period and age-related windows of susceptibility coupled with several commonly considered exposure metrics. The method is illustrated in a study of the timing of the effects of constituents of air pollution on mortality in the Nurses’ Health Study. PMID:26750582

Risk Evaluation of Multiple Hazards during Sediment and Water Related Disasters in a Small Basin

Science.gov (United States)

Yamanoi, Kazuki; Fujita, Masaharu

2016-04-01

To reduce human damage due to sediment and water related disasters induced by heavy rainfall, warning and evacuation system is very important. In Japan, the Meteorological Agency issues the sediment disaster alert when the potential of sediment disaster increases. Following the alert, local government issues evacuation advisory considering the alert and premonitory phenomena. However, it is very difficult for local people to perceive the dangerousness around them because the alert and advisory do not contain any definite information. Therefore, they sometimes misjudge the evacuation action. One reason of this is not only crucial hazards but also relatively small-scale multiple hazards take place and rise evacuation difficulties during sediment and water related disaster. Examples of small-scale hazards include: rainfall-associated hazards such as poor visibility or road submergence; landslide-associated hazards such as slope failure or sediment inflow; and flood-associated hazards such as overtopping of river dike, inundation, or destruction of bridges. The purpose of this study was to estimate the risk of multiple hazards during disaster events by numerical simulation. We applied the integrated sediment runoff model on unit channels, unit slopes, and slope units to an actual sediment and water related disaster occurred in a small basin in Tamba city, Hyogo, Japan. The maximum rainfall per hour was 91 mm (17/09/2014 2:00˜3:00) and the maximum daily precipitation was 414mm. The integrated model contains semi-physical based landslide prediction (sediment production) model, rainfall runoff model employing the kinematic wave method, model of sediment supply to channels, and bedload and suspended sediment transport model. We evaluated the risk of rainfall-associated hazards in each slope unit into 4 levels (Level I ˜ IV) using the rainfall intensity Ir [mm/hour]. The risk of flood- associated hazards were also estimated using the ratio of calculated water level and

Antidepressant sales and the risk for alcohol-related and non-alcohol-related suicide in Finland--an individual-level population study.

Science.gov (United States)

Moustgaard, Heta; Joutsenniemi, Kaisla; Myrskylä, Mikko; Martikainen, Pekka

2014-01-01

A marked decline in suicide rates has co-occurred with increased antidepressant sales in several countries but the causal connection between the trends remains debated. Most previous studies have focused on overall suicide rates and neglected differential effects in population subgroups. Our objective was to investigate whether increasing sales of non-tricyclic antidepressants have reduced alcohol- and non-alcohol-related suicide risk in different population subgroups. We followed a nationally representative sample of 950,158 Finnish adults in 1995-2007 for alcohol-related (n = 2,859) and non-alcohol-related (n = 8,632) suicides. We assessed suicide risk by gender and social group according to regional sales of non-tricyclic antidepressants, measured by sold doses per capita, prevalence of antidepressant users, and proportion of antidepressant users with doses reflecting minimally adequate treatment. Fixed-effects Poisson regression models controlled for regional differences and time trends that may influence suicide risk irrespective of antidepressant sales. The number of sold antidepressant doses per capita and the prevalence of antidepressant users were unrelated to male suicide risk. However, one percentage point increase in the proportion of antidepressant users receiving minimally adequate treatment reduced non-alcohol-related male suicide risk by one percent (relative risk 0.987, 95% confidence interval 0.976-0.998). This beneficial effect only emerged among men with high education, high income, and employment, among men without a partner, and men not owning their home. Alcohol-related suicides and female suicides were unrelated to all measures of antidepressant sales. We found little evidence that increase in overall sales or in the prevalence of non-tricyclic antidepressant users would have caused the fall in suicide rates in Finland in 1995-2007. However, the rise in the proportion of antidepressant users receiving minimally adequate treatment, possibly

Expected utility and catastrophic risk in a stochastic economy-climate model

Energy Technology Data Exchange (ETDEWEB)

Ikefuji, M. [Institute of Social and Economic Research, Osaka University, Osaka (Japan); Laeven, R.J.A.; Magnus, J.R. [Department of Econometrics and Operations Research, Tilburg University, Tilburg (Netherlands); Muris, C. [CentER, Tilburg University, Tilburg (Netherlands)

2010-11-15

In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economy-climate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

Individual-based model for radiation risk assessment

Science.gov (United States)

Smirnova, O.

A mathematical model is developed which enables one to predict the life span probability for mammals exposed to radiation. It relates statistical biometric functions with statistical and dynamic characteristics of an organism's critical system. To calculate the dynamics of the latter, the respective mathematical model is used too. This approach is applied to describe the effects of low level chronic irradiation on mice when the hematopoietic system (namely, thrombocytopoiesis) is the critical one. For identification of the joint model, experimental data on hematopoiesis in nonirradiated and irradiated mice, as well as on mortality dynamics of those in the absence of radiation are utilized. The life span probability and life span shortening predicted by the model agree with corresponding experimental data. Modeling results show the significance of ac- counting the variability of the individual radiosensitivity of critical system cells when estimating the radiation risk. These findings are corroborated by clinical data on persons involved in the elimination of the Chernobyl catastrophe after- effects. All this makes it feasible to use the model for radiation risk assessments for cosmonauts and astronauts on long-term missions such as a voyage to Mars or a lunar colony. In this case the model coefficients have to be determined by making use of the available data for humans. Scenarios for the dynamics of dose accumulation during space flights should also be taken into account.

Development of a prototype Typhoon Risk Model over the Korean Peninsula

Science.gov (United States)

Kim, K. Y.; Cocke, S.; Shin, D. W.; CHOI, M.; Kwon, J.

2016-12-01

Risk can be defined as probability of a given hazard of a given level causing a particular level of loss of damage (Alexander, 2000). Risk management is important for mitigation and developing plans for emergencies. More effective risk management strategies can help reduce potential losses from natural disasters like typhoon, floods, earthquakes, and so on. We are developing a prototype typhoon risk model to assess the current and potentially future hazard due to typhoons in the Western Pacific. To develop the typhoon risk model, a variety of sources of data over Korea are used such as population, damage to buildings, agriculture, ships, etc. The model is based on proven concepts used in catastrophe models that have been used in the U.S. and other regions of the world. Recently, the sea surface temperatures where typhoons have occurred have tended to increase. According to recent studies of global warming, the intensity of typhoons could increase, and the frequency of typhoons may decrease in the future climate. The prototype risk model can help us determine the change in risk as a consequence of the change in typhoon activity. We focus on Korea and other regions of interest to Korean insurers, re-insurers, and related industries. The model can potentially be coupled to various damage models or emergency management systems for planning and mitigation. In addition, the assessment would be useful for emergency planners, coastal community planners, and private and governmental insurance programs. This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA2016-8030.

Safety from physical viewpoint: ''two-risk model in multiple risk problem''

International Nuclear Information System (INIS)

Kuz'Min, I.I.; Akimov, V.A.

1998-01-01

Full text of publication follows: the problem of safety provision for people and environment within the framework of a certain socio-economic system (SES) as a problem of managing a great number of interacting risks characterizing numerous hazards (natural, manmade, social, economic once, etc.) inherent in the certain SES has been discussed. From the physical point of view, it can be considered a problem of interaction of many bodies which has no accurate mathematical solution even if the laws of interaction of this bodies are known. In physics, to solve this problem, an approach based on the reduction of the above-mentioned problem of the problem of two-body interaction which can be solved accurately in mathematics has been used. The report presents a similar approach to the problem of risk management in the SES. This approach includes the subdivision of numerous hazards inherent within the framework of the SES into two classes of hazards, so that each of the classes could be considered an integrated whole one, each of them being characterized by the appropriate risk. Consequently, problem of 'multiple-risk' management (i.e. the problem of many bodies, as represented in physics) can be reduced to the 'two-risk' management problem (that is, to the problem two-bodies). Within the framework of the two-risk model the optimization of costs to reduce the two kinds of risk, that is, the risk inherent in the SES as a whole, as well as the risk potentially provoked by lots of activities to be introduced in the SES economy has been described. The model has made it possible to formulate and prove the theorem of equilibrium in risk management. Using the theorem, a relatively simple and practically applicable procedure of optimizing the threshold costs to reduce diverse kinds of risk has been elaborated. The procedure provides to assess the minimum value of the cost that can be achieved regarding the socio-economic factors typical of the SES under discussion. The aimed

Risk Estimates and Risk Factors Related to Psychiatric Inpatient Suicide—An Overview

Directory of Open Access Journals (Sweden)

Trine Madsen

2017-03-01

Full Text Available People with mental illness have an increased risk of suicide. The aim of this paper is to provide an overview of suicide risk estimates among psychiatric inpatients based on the body of evidence found in scientific peer-reviewed literature; primarily focusing on the relative risks, rates, time trends, and socio-demographic and clinical risk factors of suicide in psychiatric inpatients. Psychiatric inpatients have a very high risk of suicide relative to the background population, but it remains challenging for clinicians to identify those patients that are most likely to die from suicide during admission. Most studies are based on low power, thus compromising quality and generalisability. The few studies with sufficient statistical power mainly identified non-modifiable risk predictors such as male gender, diagnosis, or recent deliberate self-harm. Also, the predictive value of these predictors is low. It would be of great benefit if future studies would be based on large samples while focusing on modifiable predictors over the course of an admission, such as hopelessness, depressive symptoms, and family/social situations. This would improve our chances of developing better risk assessment tools.

Fuzzy audit risk modeling algorithm

Directory of Open Access Journals (Sweden)

Zohreh Hajihaa

2011-07-01

Full Text Available Fuzzy logic has created suitable mathematics for making decisions in uncertain environments including professional judgments. One of the situations is to assess auditee risks. During recent years, risk based audit (RBA has been regarded as one of the main tools to fight against fraud. The main issue in RBA is to determine the overall audit risk an auditor accepts, which impact the efficiency of an audit. The primary objective of this research is to redesign the audit risk model (ARM proposed by auditing standards. The proposed model of this paper uses fuzzy inference systems (FIS based on the judgments of audit experts. The implementation of proposed fuzzy technique uses triangular fuzzy numbers to express the inputs and Mamdani method along with center of gravity are incorporated for defuzzification. The proposed model uses three FISs for audit, inherent and control risks, and there are five levels of linguistic variables for outputs. FISs include 25, 25 and 81 rules of if-then respectively and officials of Iranian audit experts confirm all the rules.

Modeling for operational event risk assessment

International Nuclear Information System (INIS)

Sattison, M.B.

1997-01-01

The U.S. Nuclear Regulatory Commission has been using risk models to evaluate the risk significance of operational events in U.S. commercial nuclear power plants for more seventeen years. During that time, the models have evolved in response to the advances in risk assessment technology and insights gained with experience. Evaluation techniques fall into two categories, initiating event assessments and condition assessments. The models used for these analyses have become uniquely specialized for just this purpose

Work-related stress risk assessment in Italy: a methodological proposal adapted to regulatory guidelines.

Science.gov (United States)

Persechino, Benedetta; Valenti, Antonio; Ronchetti, Matteo; Rondinone, Bruna Maria; Di Tecco, Cristina; Vitali, Sara; Iavicoli, Sergio

2013-06-01

Work-related stress is one of the major causes of occupational ill health. In line with the regulatory framework on occupational health and safety (OSH), adequate models for assessing and managing risk need to be identified so as to minimize the impact of this stress not only on workers' health, but also on productivity. After close analysis of the Italian and European reference regulatory framework and work-related stress assessment and management models used in some European countries, we adopted the UK Health and Safety Executive's (HSE) Management Standards (MS) approach, adapting it to the Italian context in order to provide a suitable methodological proposal for Italy. We have developed a work-related stress risk assessment strategy, meeting regulatory requirements, now available on a specific web platform that includes software, tutorials, and other tools to assist companies in their assessments. This methodological proposal is new on the Italian work-related stress risk assessment scene. Besides providing an evaluation approach using scientifically validated instruments, it ensures the active participation of occupational health professionals in each company. The assessment tools provided enable companies not only to comply with the law, but also to contribute to a database for monitoring and assessment and give access to a reserved area for data analysis and comparisons.

Risk factors for age-related maculopathy.

Science.gov (United States)

Connell, Paul P; Keane, Pearse A; O'Neill, Evelyn C; Altaie, Rasha W; Loane, Edward; Neelam, Kumari; Nolan, John M; Beatty, Stephen

2009-01-01

Age-related maculopathy (ARM) is the leading cause of blindness in the elderly. Although beneficial therapeutic strategies have recently begun to emerge, much remains unclear regarding the etiopathogenesis of this disorder. Epidemiologic studies have enhanced our understanding of ARM, but the data, often conflicting, has led to difficulties with drawing firm conclusions with respect to risk for this condition. As a consequence, we saw a need to assimilate the published findings with respect to risk factors for ARM, through a review of the literature appraising results from published cross-sectional studies, prospective cohort studies, case series, and case control studies investigating risk for this condition. Our review shows that, to date, and across a spectrum of epidemiologic study designs, only age, cigarette smoking, and family history of ARM have been consistently demonstrated to represent risk for this condition. In addition, genetic studies have recently implicated many genes in the pathogenesis of age-related maculopathy, including Complement Factor H, PLEKHA 1, and LOC387715/HTRA1, demonstrating that environmental and genetic factors are important for the development of ARM suggesting that gene-environment interaction plays an important role in the pathogenesis of this condition.

Risk Factors for Age-Related Maculopathy

Directory of Open Access Journals (Sweden)

Paul P. Connell

2009-01-01

Full Text Available Age-related maculopathy (ARM is the leading cause of blindness in the elderly. Although beneficial therapeutic strategies have recently begun to emerge, much remains unclear regarding the etiopathogenesis of this disorder. Epidemiologic studies have enhanced our understanding of ARM, but the data, often conflicting, has led to difficulties with drawing firm conclusions with respect to risk for this condition. As a consequence, we saw a need to assimilate the published findings with respect to risk factors for ARM, through a review of the literature appraising results from published cross-sectional studies, prospective cohort studies, case series, and case control studies investigating risk for this condition. Our review shows that, to date, and across a spectrum of epidemiologic study designs, only age, cigarette smoking, and family history of ARM have been consistently demonstrated to represent risk for this condition. In addition, genetic studies have recently implicated many genes in the pathogenesis of age-related maculopathy, including Complement Factor H, PLEKHA 1, and LOC387715/HTRA1, demonstrating that environmental and genetic factors are important for the development of ARM suggesting that gene-environment interaction plays an important role in the pathogenesis of this condition.

Risk factors for age-related maculopathy.

LENUS (Irish Health Repository)

Connell, Paul P

2012-02-01

Age-related maculopathy (ARM) is the leading cause of blindness in the elderly. Although beneficial therapeutic strategies have recently begun to emerge, much remains unclear regarding the etiopathogenesis of this disorder. Epidemiologic studies have enhanced our understanding of ARM, but the data, often conflicting, has led to difficulties with drawing firm conclusions with respect to risk for this condition. As a consequence, we saw a need to assimilate the published findings with respect to risk factors for ARM, through a review of the literature appraising results from published cross-sectional studies, prospective cohort studies, case series, and case control studies investigating risk for this condition. Our review shows that, to date, and across a spectrum of epidemiologic study designs, only age, cigarette smoking, and family history of ARM have been consistently demonstrated to represent risk for this condition. In addition, genetic studies have recently implicated many genes in the pathogenesis of age-related maculopathy, including Complement Factor H, PLEKHA 1, and LOC387715\\/HTRA1, demonstrating that environmental and genetic factors are important for the development of ARM suggesting that gene-environment interaction plays an important role in the pathogenesis of this condition.

MODELING CREDIT RISK THROUGH CREDIT SCORING

OpenAIRE

Adrian Cantemir CALIN; Oana Cristina POPOVICI

2014-01-01

Credit risk governs all financial transactions and it is defined as the risk of suffering a loss due to certain shifts in the credit quality of a counterpart. Credit risk literature gravitates around two main modeling approaches: the structural approach and the reduced form approach. In addition to these perspectives, credit risk assessment has been conducted through a series of techniques such as credit scoring models, which form the traditional approach. This paper examines the evolution of...

Risk assessment to an integrated planning model for UST programs

International Nuclear Information System (INIS)

Ferguson, K.W.

1993-01-01

The US Postal Service maintains the largest civilian fleet in the United States totaling approximately 180,000 vehicles. To support the fleets daily energy requirements, the Postal Service also operates one of the largest networks of underground storage tanks nearly 7,500 nationwide. A program to apply risk assessment to planning, budget development and other management actions was implemented during September, 1989. Working closely with a consultant, the postal service developed regulatory and environmental risk criteria and weighting factors for a ranking model. The primary objective was to identify relative risks for each underground tank at individual facilities. Relative risks at each facility were determined central to prioritizing scheduled improvements to the tank network. The survey was conducted on 302 underground tanks in the Northeast Region of the US. An environmental and regulatory risk score was computed for each UST. By ranking the tanks according to their risk score, tanks were classified into management action categories including, but the limited to, underground tank testing, retrofit, repair, replacement and closure

A systematic review of risk and protective factors associated with family related violence in refugee families

DEFF Research Database (Denmark)

Timshel, Isabelle; Montgomery, Edith; Dalgaard, Nina Thorup

2017-01-01

and protective factors an ecological model was used to structure the findings. At the individual level, parental trauma experiences/mental illness, substance abuse and history of child abuse were found to be risk factors. Family level risk factors included parent-child interaction, family structure and family...... families is a result of accumulating, multiple risk factors on the individual, familial, societal and cultural level. The findings suggest that individual trauma and exile related stress do not only affect the individual but have consequences at a family level. Thus, interventions targeting family related...

Risk modelling study for carotid endarterectomy.

Science.gov (United States)

Kuhan, G; Gardiner, E D; Abidia, A F; Chetter, I C; Renwick, P M; Johnson, B F; Wilkinson, A R; McCollum, P T

2001-12-01

The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

The acquired preparedness risk model applied to smoking in 5th grade children.

Science.gov (United States)

Combs, Jessica L; Spillane, Nichea S; Caudill, Leann; Stark, Brittany; Smith, Gregory T

2012-03-01

The very early onset of smoking predicts numerous health problems. The authors conducted the first test of one risk model for elementary school age smoking, known as the acquired preparedness (AP) model of risk, in a cross-sectional sample of 309 5th grade children. The model posits that (a) impulsivity-related personality traits contribute to risk for a variety of risky, maladaptive behaviors; (b) smoking expectancies confer risk only for smoking; and (c) the personality traits contribute to the formation of high risk expectancies for reinforcement from smoking, which in turn increases the likelihood of early onset smoking. The model was supported: the high-risk personality traits distinguished children engaging in any risky, maladaptive behavior from other children, and the smoking expectancies differentiated smokers from all other children. The relationship between personality tendencies to act rashly when experiencing intense positive or negative emotions and smoker status was partially mediated by expectancies for reinforcement from smoking. This model should be investigated longitudinally. Copyright © 2011. Published by Elsevier Ltd.

Integrated source-risk model for radon: A definition study

International Nuclear Information System (INIS)

Laheij, G.M.H.; Aldenkamp, F.J.; Stoop, P.

1993-10-01

The purpose of a source-risk model is to support policy making on radon mitigation by comparing effects of various policy options and to enable optimization of counter measures applied to different parts of the source-risk chain. There are several advantages developing and using a source-risk model: risk calculations are standardized; the effects of measures applied to different parts of the source-risk chain can be better compared because interactions are included; and sensitivity analyses can be used to determine the most important parameters within the total source-risk chain. After an inventory of processes and sources to be included in the source-risk chain, the models presently available in the Netherlands are investigated. The models were screened for completeness, validation and operational status. The investigation made clear that, by choosing for each part of the source-risk chain the most convenient model, a source-risk chain model for radon may be realized. However, the calculation of dose out of the radon concentrations and the status of the validation of most models should be improved. Calculations with the proposed source-risk model will give estimations with a large uncertainty at the moment. For further development of the source-risk model an interaction between the source-risk model and experimental research is recommended. Organisational forms of the source-risk model are discussed. A source-risk model in which only simple models are included is also recommended. The other models are operated and administrated by the model owners. The model owners execute their models for a combination of input parameters. The output of the models is stored in a database which will be used for calculations with the source-risk model. 5 figs., 15 tabs., 7 appendices, 14 refs

Risk predictive modelling for diabetes and cardiovascular disease.

Science.gov (United States)

Kengne, Andre Pascal; Masconi, Katya; Mbanya, Vivian Nchanchou; Lekoubou, Alain; Echouffo-Tcheugui, Justin Basile; Matsha, Tandi E

2014-02-01

Absolute risk models or clinical prediction models have been incorporated in guidelines, and are increasingly advocated as tools to assist risk stratification and guide prevention and treatments decisions relating to common health conditions such as cardiovascular disease (CVD) and diabetes mellitus. We have reviewed the historical development and principles of prediction research, including their statistical underpinning, as well as implications for routine practice, with a focus on predictive modelling for CVD and diabetes. Predictive modelling for CVD risk, which has developed over the last five decades, has been largely influenced by the Framingham Heart Study investigators, while it is only ∼20 years ago that similar efforts were started in the field of diabetes. Identification of predictive factors is an important preliminary step which provides the knowledge base on potential predictors to be tested for inclusion during the statistical derivation of the final model. The derived models must then be tested both on the development sample (internal validation) and on other populations in different settings (external validation). Updating procedures (e.g. recalibration) should be used to improve the performance of models that fail the tests of external validation. Ultimately, the effect of introducing validated models in routine practice on the process and outcomes of care as well as its cost-effectiveness should be tested in impact studies before wide dissemination of models beyond the research context. Several predictions models have been developed for CVD or diabetes, but very few have been externally validated or tested in impact studies, and their comparative performance has yet to be fully assessed. A shift of focus from developing new CVD or diabetes prediction models to validating the existing ones will improve their adoption in routine practice.

Quantitative occupational risk model: Single hazard

International Nuclear Information System (INIS)

Papazoglou, I.A.; Aneziris, O.N.; Bellamy, L.J.; Ale, B.J.M.; Oh, J.

2017-01-01

A model for the quantification of occupational risk of a worker exposed to a single hazard is presented. The model connects the working conditions and worker behaviour to the probability of an accident resulting into one of three types of consequence: recoverable injury, permanent injury and death. Working conditions and safety barriers in place to reduce the likelihood of an accident are included. Logical connections are modelled through an influence diagram. Quantification of the model is based on two sources of information: a) number of accidents observed over a period of time and b) assessment of exposure data of activities and working conditions over the same period of time and the same working population. Effectiveness of risk reducing measures affecting the working conditions, worker behaviour and/or safety barriers can be quantified through the effect of these measures on occupational risk. - Highlights: • Quantification of occupational risk from a single hazard. • Influence diagram connects working conditions, worker behaviour and safety barriers. • Necessary data include the number of accidents and the total exposure of worker • Effectiveness of risk reducing measures is quantified through the impact on the risk • An example illustrates the methodology.

School-related risk factors for drunkenness among adolescents: risk factors differ between socio-economic groups

DEFF Research Database (Denmark)

Andersen, Anette; Holstein, Bjørn E; Due, Pernille

2006-01-01

Purpose: To examine, separately for boys and girls, whether socio-economic differences in drunkenness exist in adolescence, whether the level of exposure to school-related risk factors differ between socio-economic groups, and whether the relative contribution of school-related risk factors......) was measured by parental occupation. RESULTS: Among girls, exposures to school-related risk factors were more prevalent in lower socio-economic groups. Poor school satisfaction was associated with drunkenness among girls from high SEP, odds ratio (OR) = 2.98 (0.73-12.16). Among boys from high SEP autonomy...

A systematic review of risk and protective factors associated with family related violence in refugee families.

Science.gov (United States)

Timshel, Isabelle; Montgomery, Edith; Dalgaard, Nina Thorup

2017-08-01

The current systematic review summarizes the evidence from studies examining the risk and protective factors associated with family related violence in refugee families. Data included 15 peer-reviewed qualitative and quantitative studies. In order to gain an overview of the identified risk and protective factors an ecological model was used to structure the findings. At the individual level, parental trauma experiences/mental illness, substance abuse and history of child abuse were found to be risk factors. Family level risk factors included parent-child interaction, family structure and family acculturation stress. At the societal level low socioeconomic status was identified as a risk factor. Cultural level risk factors included patriarchal beliefs. Positive parental coping strategies were a protective factor. An ecological analysis of the results suggests that family related violence in refugee families is a result of accumulating, multiple risk factors on the individual, familial, societal and cultural level. The findings suggest that individual trauma and exile related stress do not only affect the individual but have consequences at a family level. Thus, interventions targeting family related violence should not only include the individual, but the family. Copyright © 2017 Elsevier Ltd. All rights reserved.

Farm Work-Related Injuries and Risk Factors in South Korean Agriculture.

Science.gov (United States)

Kim, Hyocher; Räsänen, Kimmo; Chae, Hyeseon; Kim, Kyungsu; Kim, Kyungran; Lee, Kyungsuk

2016-01-01

Agriculture is known to be a risk-filled industry in South Korea, as it is worldwide. The aims of this study were to identify the magnitude of farm work-related injuries and evaluate the association between injury and possible risk factors. Farmers, including farm members (N = 16,160), were surveyed. After excluding 7 subjects with missing data in questions about injury, 16,153 farmer responses were used for the analysis. Of the 16,153 farmers, 3.6% answered having at least one farm work-related injury requiring outpatient treatment or hospitalization during 2012. The proportion of injured men (4.3%) was 1.5 times higher than women (2.9%). From an age perspective, the proportion was 1.3% of those aged 49 or below, 2.7% of those aged 50-59, 4.2% of those aged 60-69, 4.2% of those aged 70-79, and 3.1% of those aged 80 or above. We used a multivariate logistic regression analysis with a stepwise model (forward) for risk factors (gender, age, farm ownership, farm type, work years in agriculture, work months during 2012, night work experience, and work experience under the influence of alcohol). The increased risk of farm work-related injuries significantly remained associated with age, farm ownership, and experience of night work. Further studies should be conducted to consistently identify injury characteristics, especially for old farmers, considering the crop cultivation in Asian countries.

[An experimental model for assessing the risk factors for work-related stress in four Italian universities].

Science.gov (United States)

Miscetti, G; Barberini, L; Chiocchini, D; Cirimbilli, A; Pippi, R; Pampanella, L; Caserta, G; Gargarella, L

2011-01-01

This study, a collaborative effort among the Local Health Authority 2 of Perugia, Italy, the National Coordination of Worker's Safety Representatives for University and Research Institutions and the National Coordination for Protection and Prevention Services for Universities and Research Institutions, describes the results of a method used to evaluate work-related stress. Personnel from four Italian universities, which we call University I, II, III and IV geographically distributed in nord (1), center (2) and south (1) of Italy, responded to a questionnaire regarding risk evaluation of work-related stress in response to the Italian Law 81/2008. The methodology includes a preliminary analysis of the physical/technological and organizational/relational aspects of the company in order to determine a risk factor of work-related stress. This is followed by an evaluation by agencies competent in the areas of prevention and protection, (Administrative personnel of the company, Medical support persons, heads of the Prevention and Protection Service, employee representatives, and others) that apply a specific algorithm and by the employees through the completion of a questionnaire. The employees, mostly men, of the various universities, completed 510 questionnaires. Based on the results of the questionnaires and on a comparison between the expectations of the administration and the employees, the preventative measures that need to be adopted were identified. The results of this study show that there is not complete agreement between the administration and the employees regarding the work-related expectations. This difference in viewpoints could be a source of work-related stress. Some aspects of the study were shown to be of common concern in the various universities, while for other aspects, there were significantly different perceptions between male and female employees. An immediate response is needed with respect to some aspects in the work context and to plan further

The relation of risk assessment and health impact assessment

DEFF Research Database (Denmark)

Ádám, Balázs; Gulis, Gabriel

2013-01-01

than assessing a present situation. As part of this process, however, methods applied in risk assessment are used. Risk assessment typically characterises relation of a well-defined risk factor to a well-defined health outcome. Within HIA usually several individual risk assessments are needed...... of the causal chain from the proposal through related health determinants and risk factors to health outcomes. The stepwise analysis, systematic prioritization and consideration of horizontal interactions between the causal pathways make it feasible to use widely recognized risk assessment methods in the HIA......The level and distribution of health risks in a society is substantially influenced by measures of various policies, programmes or projects. Risk assessment can evaluate the nature, likelihood and severity of an adverse effect. Health impact assessment (HIA) provides similar function when used...

Study of dose and relative risk of occupationally exposed individuals in interventional procedures

International Nuclear Information System (INIS)

Silveira Filho, Jose A.M.; Reis, Charlene O.; Taniguti, Lana T.; Pacifico, Leonardo C.; SaintYves, Thalis L.A.; Mecca, Fernando A.

2012-01-01

This paper estimates the occupational effective dose and the relative risk of leukemia and cancers of the digestive tract mortality through dose study of the most radiosensitive anatomical regions (lens, thyroid, chest and gonads) of the professionals involved in interventional gonad procedures. It was considered a cumulative exposure time of 10,000 hours, which is the occupational exposure time of an IOE in throughout his professional life. It was also considered that they always use Personal Protective Equipment (PPE). Mathematical models derived from epidemiological data contained in the BEIR V and in the IAEA’s TECDOC 870 are used to estimate the relative risk. The results show a significant increase in mortality risk for these types of cancer for individuals occupationally exposed to three different distances from the x-ray beam, and reinforces that radiation protection measures are essential. (author)

A model-based risk management framework

Energy Technology Data Exchange (ETDEWEB)

Gran, Bjoern Axel; Fredriksen, Rune

2002-08-15

The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

The bystander effect model of Brenner and Sachs fitted to lung cancer data in 11 cohorts of underground miners, and equivalence of fit of a linear relative risk model with adjustment for attained age and age at exposure

International Nuclear Information System (INIS)

Little, M P

2004-01-01

Bystander effects following exposure to α-particles have been observed in many experimental systems, and imply that linearly extrapolating low dose risks from high dose data might materially underestimate risk. Brenner and Sachs (2002 Int. J. Radiat. Biol. 78 593-604; 2003 Health Phys. 85 103-8) have recently proposed a model of the bystander effect which they use to explain the inverse dose rate effect observed for lung cancer in underground miners exposed to radon daughters. In this paper we fit the model of the bystander effect proposed by Brenner and Sachs to 11 cohorts of underground miners, taking account of the covariance structure of the data and the period of latency between the development of the first pre-malignant cell and clinically overt cancer. We also fitted a simple linear relative risk model, with adjustment for age at exposure and attained age. The methods that we use for fitting both models are different from those used by Brenner and Sachs, in particular taking account of the covariance structure, which they did not, and omitting certain unjustifiable adjustments to the miner data. The fit of the original model of Brenner and Sachs (with 0 y period of latency) is generally poor, although it is much improved by assuming a 5 or 6 y period of latency from the first appearance of a pre-malignant cell to cancer. The fit of this latter model is equivalent to that of a linear relative risk model with adjustment for age at exposure and attained age. In particular, both models are capable of describing the observed inverse dose rate effect in this data set

Breast cancer risk in atomic bomb survivors from multi-model inference with incidence data 1958-1998

International Nuclear Information System (INIS)

Kaiser, J.C.; Jacob, P.; Meckbach, R.; Cullings, H.M.

2012-01-01

Breast cancer risk from radiation exposure has been analyzed in the cohort of Japanese a-bomb survivors using empirical models and mechanistic two-step clonal expansion (TSCE) models with incidence data from 1958 to 1998. TSCE models rely on a phenomenological representation of cell transition processes on the path to cancer. They describe the data as good as empirical models and this fact has been exploited for risk assessment. Adequate models of both types have been selected with a statistical protocol based on parsimonious parameter deployment and their risk estimates have been combined using multi-model inference techniques. TSCE models relate the radiation risk to cell processes which are controlled by age-increasing rates of initiating mutations and by changes in hormone levels due to menopause. For exposure at young age, they predict an enhanced excess relative risk (ERR) whereas the preferred empirical model shows no dependence on age at exposure. At attained age 70, the multi-model median of the ERR at 1 Gy decreases moderately from 1.2 Gy"-"1 (90% CI 0.72; 2.1) for exposure at age 25 to a 30% lower value for exposure at age 55. For cohort strata with few cases, where model predictions diverge, uncertainty intervals from multi-model inference are enhanced by up to a factor of 1.6 compared to the preferred empirical model. Multi-model inference provides a joint risk estimate from several plausible models rather than relying on a single model of choice. It produces more reliable point estimates and improves the characterization of uncertainties. The method is recommended for risk assessment in practical radiation protection. (orig.)

Breast cancer risk in atomic bomb survivors from multi-model inference with incidence data 1958-1998

Energy Technology Data Exchange (ETDEWEB)

Kaiser, J.C.; Jacob, P.; Meckbach, R. [Institute of Radiation Protection, Helmholtz-Zentrum Muenchen, German Research Centre for Environmental Health, Neuherberg (Germany); Cullings, H.M. [Radiation Effects Research Foundation, Department of Statistics, Hiroshima (Japan)

2012-03-15

Breast cancer risk from radiation exposure has been analyzed in the cohort of Japanese a-bomb survivors using empirical models and mechanistic two-step clonal expansion (TSCE) models with incidence data from 1958 to 1998. TSCE models rely on a phenomenological representation of cell transition processes on the path to cancer. They describe the data as good as empirical models and this fact has been exploited for risk assessment. Adequate models of both types have been selected with a statistical protocol based on parsimonious parameter deployment and their risk estimates have been combined using multi-model inference techniques. TSCE models relate the radiation risk to cell processes which are controlled by age-increasing rates of initiating mutations and by changes in hormone levels due to menopause. For exposure at young age, they predict an enhanced excess relative risk (ERR) whereas the preferred empirical model shows no dependence on age at exposure. At attained age 70, the multi-model median of the ERR at 1 Gy decreases moderately from 1.2 Gy{sup -1} (90% CI 0.72; 2.1) for exposure at age 25 to a 30% lower value for exposure at age 55. For cohort strata with few cases, where model predictions diverge, uncertainty intervals from multi-model inference are enhanced by up to a factor of 1.6 compared to the preferred empirical model. Multi-model inference provides a joint risk estimate from several plausible models rather than relying on a single model of choice. It produces more reliable point estimates and improves the characterization of uncertainties. The method is recommended for risk assessment in practical radiation protection. (orig.)

Potential mediating pathways through which sports participation relates to reduced risk of suicidal ideation.

Science.gov (United States)

Taliaferro, Lindsay A; Rienzo, Barbara A; Miller, M David; Pigg, R Morgan; Dodd, Virginia J

2010-09-01

Suicide ranks as the third leading cause of death for American youth. Researchers examining sport participation and suicidal behavior have regularly found inverse relationships. This study represents the first effort to test a model depicting potential mechanisms through which sport participation relates to reduced risk of suicidal ideation. The participants were 450 undergraduate students. Measures assessed participants' involvement in university-run sports and other activities; frequency of physical activity; and perceived social support, self-esteem, depression, hopelessness, loneliness, and suicidal ideation. Regression analyses confirmed a path model and tested for mediation effects. Vigorous activity mediated relationships between sport participation and self-esteem and depression; and self-esteem and depression mediated the relationship between vigorous activity and suicidal ideation. Social support mediated relationships between sport participation and depression, hopelessness, and loneliness; and each of these risk factors partially mediated the relationship between social support and suicidal ideation. However no variable fully mediated the relationship between sport participation and suicidal ideation. This study provides a foundation for research designed to examine pathways through which sport participation relates to reduced risk of suicidal behavior.

Development of Toxicological Risk Assessment Models for Acute and Chronic Exposure to Pollutants

Directory of Open Access Journals (Sweden)

Elke S. Reichwaldt

2016-08-01

Full Text Available Alert level frameworks advise agencies on a sequence of monitoring and management actions, and are implemented so as to reduce the risk of the public coming into contact with hazardous substances. Their effectiveness relies on the detection of the hazard, but with many systems not receiving any regular monitoring, pollution events often go undetected. We developed toxicological risk assessment models for acute and chronic exposure to pollutants that incorporate the probabilities that the public will come into contact with undetected pollution events, to identify the level of risk a system poses in regards to the pollutant. As a proof of concept, we successfully demonstrated that the models could be applied to determine probabilities of acute and chronic illness types related to recreational activities in waterbodies containing cyanotoxins. Using the acute model, we identified lakes that present a ‘high’ risk to develop Day Away From Work illness, and lakes that present a ‘low’ or ‘medium’ risk to develop First Aid Cases when used for swimming. The developed risk models succeeded in categorising lakes according to their risk level to the public in an objective way. Modelling by how much the probability of public exposure has to decrease to lower the risks to acceptable levels will enable authorities to identify suitable control measures and monitoring strategies. We suggest broadening the application of these models to other contaminants.

Sector model analysis of risk on cross-jurisdictional treatment of disaster waste related to the Great East Japan Earthquake

International Nuclear Information System (INIS)

Nagashima, Miori; Itokawa, Etsuko; Ozuka, Yohei

2012-01-01

This study addressed the controversial issue of disaster waste treatment in the reconstruction efforts following the Great East Japan Earthquake. Using the Sector Model (Matsumoto 2009), we categorized a range of actions taken in relation to the cross-jurisdictional treatment into the four sectors, government, industry, academia, and private. The analysis through this Sector Model made it possible to map the entire layout of waste treatment, inclusive of less-visible industry and academia sectors. Accordingly, we have argued that differences of risk awareness are not necessarily due to sector differences but rather depend on two aspects of the disaster waste treatment; the safety levels and the nationwide treatment of waste in Japan. We further suggest that the discrepancy in the arguments on safety levels emerged as a result of scientific under-determination and cross-jurisdictional treatment from social and/or political under-determination. (author)

Default risk modeling beyond the first-passage approximation: Extended Black-Cox model

Science.gov (United States)

Katz, Yuri A.; Shokhirev, Nikolai V.

2010-07-01

We develop a generalization of the Black-Cox structural model of default risk. The extended model captures uncertainty related to firm’s ability to avoid default even if company’s liabilities momentarily exceeding its assets. Diffusion in a linear potential with the radiation boundary condition is used to mimic a company’s default process. The exact solution of the corresponding Fokker-Planck equation allows for derivation of analytical expressions for the cumulative probability of default and the relevant hazard rate. Obtained closed formulas fit well the historical data on global corporate defaults and demonstrate the split behavior of credit spreads for bonds of companies in different categories of speculative-grade ratings with varying time to maturity. Introduction of the finite rate of default at the boundary improves valuation of credit risk for short time horizons, which is the key advantage of the proposed model. We also consider the influence of uncertainty in the initial distance to the default barrier on the outcome of the model and demonstrate that this additional source of incomplete information may be responsible for nonzero credit spreads for bonds with very short time to maturity.

Time-related factors in the study of risks in animals and humans

International Nuclear Information System (INIS)

Gilbert, E.S.; Park, J.F.; Buschbom, R.L.

1989-01-01

Data from epidemiological studies of humans exposed to potentially harmful substances are usually analyzed using methods that account for the dependence of risks on time-related factors such as age and follow-up period. Recently developed statistical procedures allow modeling of the age-specific risks as a function of dose as well as factors such as age at exposure, time since exposure, exposure duration, and dose rate. These procedures potentially allow more rigorous inferences and clearer understanding of the patterns of risk observed in epidemiological studies than has been available in the past. Statistical procedures that consider time-related factors can also be applied to laboratory animal data, providing information that is useful for the problems involved in extrapolating from animal studies to humans. By applying such procedures to data on exposure to the same substance in different species (including humans) or to different substances in the same species, better understanding of the relationship of risks across species and across substances can be achieved. In addition, such statistical procedures allow appropriate treatment of exposure that is accumulated over time and lead to improved understanding of patterns of risk over time. The approach is illustrated using data from a lifespan study of beagle dogs exposed to inhaled Pu

Time-related factors in the study of risks in animals and man

International Nuclear Information System (INIS)

Gilbert, E.S.; Park, J.F.; Buschbom, R.L.

1988-01-01

Data from epidemiological studies of humans exposed to potentially harmful substances are usually analyzed using methods that account for the dependence of risks on time-related factors such as age and follow-up period. Recently developed statistical procedures allow modeling of the age-specific risks as a function of dose as well as factors such as age at exposure, time from exposure, exposure duration, and dose rate. These procedures potentially allow more rigorous inferences and clearer understanding of the patterns of risks observed in epidemiological studies than has been available in the past. Statistical procedures that consider time-related factors can also be applied to laboratory animal data, and provide information that is useful for the problem of extrapolating from animal studies to humans. By applying such procedures to data on exposure to the same substance in different species (including humans) or to different substances in the same species, a better understanding of the relationship of risks across species and across substances can be achieved. In addition, such statistical procedures allow appropriate treatment of exposure that is accumulated over time and lead to improved understanding of patterns of risk over time. The approach is illustrated using data from a lifespan study of beagle dogs exposed to inhaled plutonium. 12 refs., 1 fig., 3 tabs

Anemia risk in relation to lead exposure in lead-related manufacturing

Directory of Open Access Journals (Sweden)

Nan-Hung Hsieh

2017-05-01

Full Text Available Abstract Background Lead-exposed workers may suffer adverse health effects under the currently regulated blood lead (BPb levels. However, a probabilistic assessment about lead exposure-associated anemia risk is lacking. The goal of this study was to examine the association between lead exposure and anemia risk among factory workers in Taiwan. Methods We first collated BPb and indicators of hematopoietic function data via health examination records that included 533 male and 218 female lead-exposed workers between 2012 and 2014. We used benchmark dose (BMD modeling to estimate the critical effect doses for detection of abnormal indicators. A risk-based probabilistic model was used to characterize the potential hazard of lead poisoning for job-specific workers by hazard index (HI. We applied Bayesian decision analysis to determine whether BMD could be implicated as a suitable BPb standard. Results Our results indicated that HI for total lead-exposed workers was 0.78 (95% confidence interval: 0.50–1.26 with risk occurrence probability of 11.1%. The abnormal risk of anemia indicators for male and female workers could be reduced, respectively, by 67–77% and 86–95% by adopting the suggested BPb standards of 25 and 15 μg/dL. Conclusions We conclude that cumulative exposure to lead in the workplace was significantly associated with anemia risk. This study suggests that current BPb standard needs to be better understood for the application of lead-exposed population protection in different scenarios to provide a novel standard for health management. Low-level lead exposure risk is an occupational and public health problem that should be paid more attention.

Antidepressant Sales and the Risk for Alcohol-Related and Non-Alcohol-Related Suicide in Finland—An Individual-Level Population Study

Science.gov (United States)

Moustgaard, Heta; Joutsenniemi, Kaisla; Myrskylä, Mikko; Martikainen, Pekka

2014-01-01

Objectives A marked decline in suicide rates has co-occurred with increased antidepressant sales in several countries but the causal connection between the trends remains debated. Most previous studies have focused on overall suicide rates and neglected differential effects in population subgroups. Our objective was to investigate whether increasing sales of non-tricyclic antidepressants have reduced alcohol- and non-alcohol-related suicide risk in different population subgroups. Methods We followed a nationally representative sample of 950,158 Finnish adults in 1995–2007 for alcohol-related (n = 2,859) and non-alcohol-related (n = 8,632) suicides. We assessed suicide risk by gender and social group according to regional sales of non-tricyclic antidepressants, measured by sold doses per capita, prevalence of antidepressant users, and proportion of antidepressant users with doses reflecting minimally adequate treatment. Fixed-effects Poisson regression models controlled for regional differences and time trends that may influence suicide risk irrespective of antidepressant sales. Results The number of sold antidepressant doses per capita and the prevalence of antidepressant users were unrelated to male suicide risk. However, one percentage point increase in the proportion of antidepressant users receiving minimally adequate treatment reduced non-alcohol-related male suicide risk by one percent (relative risk 0.987, 95% confidence interval 0.976–0.998). This beneficial effect only emerged among men with high education, high income, and employment, among men without a partner, and men not owning their home. Alcohol-related suicides and female suicides were unrelated to all measures of antidepressant sales. Conclusion We found little evidence that increase in overall sales or in the prevalence of non-tricyclic antidepressant users would have caused the fall in suicide rates in Finland in 1995–2007. However, the rise in the proportion of antidepressant

Challenges of Modeling Flood Risk at Large Scales

Science.gov (United States)

Guin, J.; Simic, M.; Rowe, J.

2009-04-01

uncertainty can be attributed to various sources among which are imperfections in the hazard modeling, inherent errors in the DTM, lack of accurate information on the properties that are being analyzed, imperfections in the vulnerability relationships, inability of the model to account for local mitigation measures that are usually undertaken when a real event is unfolding and lack of details in the claims data that are used for model calibration. Nevertheless, the model once calibrated provides a very robust framework for analyzing relative and absolute risk. The paper concludes with key economic statistics of flood risk for Great Britain as a whole including certain large loss-causing scenarios affecting the greater London region. The model estimates a total financial loss of 5.6 billion GBP to all properties at a 1% annual aggregate exceedance probability level.

Climate risk assessment in museums : degradation risks determined from temperature and relative humidity data

NARCIS (Netherlands)

Martens, M.H.J.

2012-01-01

The main subject of this thesis is the determination of climate risks to objects in museums on the basis of measured and/or simulated temperature and relative humidity data. The focus is on the quantification of climate related risks for the preservation quality of indoor climate in Dutch museums.

Forecasting Model of Risk of Cancer in Lung Cancer Pedigree in a Case-control Study

Directory of Open Access Journals (Sweden)

Huan LIN

2011-07-01

Full Text Available Background and objective Annual lung screening using spiral computed tomography (CT, has a high sensitivity of detecting early lung cancer (LC, but its high rates of false-positive often lead to unnecessary surgery. The aim of this study is to create a forecasting model of high risk individuals to lung cancer. Methods The pathologic diagnoses of LC in Guangdong Lung Cancer Institute were consecutively chosen as the probands. All the members of the first-degree relatives of probands' and their spouses' were enrolled in this study. These pedigrees consisted of 633 probands' pedigrees and 565 spouses' pedigrees. Unless otherwise stated, analyses were performed using the SPSS 17.0 statistical software package. Results Compared with the control, a family history of carcinoma in first-degree relatives was significantly associated with LC risk (OR=1.71, P<0.001, the sub-group of either one infected individual or more than two infected individuals in first-degree relatives showed significantly statistical differences (P=0.005, P=0.002. In the forecasting model, the risk compared to that in Chinese population was from 0.38 to 63.08 folds. In the population whose risk was more than 10 times to the Chinese population, the accuracy rate of prediction was 88.1%. Conclusion A family history of carcinoma in first-degree relatives was significantly associated with increased LC risk. The more infected individuals exist in first-degree relatives, the more risk was showed. In the forecasting model, smokers especially heavy ones whose risk were more than 10 times to the Chinese population should be receive annual screening. The population are positive at least any two conditions which including male, lung disease history, occupation expose and history of cancer in first-degree relative.

Risk management model of winter navigation operations

International Nuclear Information System (INIS)

Valdez Banda, Osiris A.; Goerlandt, Floris; Kuzmin, Vladimir; Kujala, Pentti; Montewka, Jakub

2016-01-01

The wintertime maritime traffic operations in the Gulf of Finland are managed through the Finnish–Swedish Winter Navigation System. This establishes the requirements and limitations for the vessels navigating when ice covers this area. During winter navigation in the Gulf of Finland, the largest risk stems from accidental ship collisions which may also trigger oil spills. In this article, a model for managing the risk of winter navigation operations is presented. The model analyses the probability of oil spills derived from collisions involving oil tanker vessels and other vessel types. The model structure is based on the steps provided in the Formal Safety Assessment (FSA) by the International Maritime Organization (IMO) and adapted into a Bayesian Network model. The results indicate that ship independent navigation and convoys are the operations with higher probability of oil spills. Minor spills are most probable, while major oil spills found very unlikely but possible. - Highlights: •A model to assess and manage the risk of winter navigation operations is proposed. •The risks of oil spills in winter navigation in the Gulf of Finland are analysed. •The model assesses and prioritizes actions to control the risk of the operations. •The model suggests navigational training as the most efficient risk control option.

Evaluation of energy related risk acceptance (APHA energy task force)

International Nuclear Information System (INIS)

Hull, A.P.

1977-01-01

Living in a technological society with large energy requirements involves a number of related actities with attendant health risks, both to the working and to the general public. Therefore, the formulation of some general principles for risk acceptance is necessary. In addition to maximizing benefits and minimizing risk, relevant considerations must be made about the perception of risk as voluntary or involuntary, the number of persons collectively at risk at any one occasion, and the extent to which a risk is a familiar one. With regard to a given benefit, such as a given amount of energy, comparisons of the risks of alternate modes of production may be utilized. However, cost-benefit consideration is essential to the amelioration of current or prospective risks. This is unusual, since it is based on some estimate of the monetary value per premature death averted. It is proposed that increased longevity would be a more satisfactory measure. On a societal basis, large expenditures for additional energy-related pollution control do not appear justifiable since much larger, nonenergy-related health risks are relatively underaddressed. Knowledgeable health professionals could benefit the public by imparting authoritative information in this area

Consumption of Sugars, Sugary Foods and Sugary Beverages in Relation to Adiposity-Related Cancer Risk in the Framingham Offspring Cohort (1991-2013).

Science.gov (United States)

Makarem, Nour; Bandera, Elisa V; Lin, Yong; Jacques, Paul; Hayes, Richard B; Parekh, Niyati

2018-04-19

Higher sugar consumption may increase cancer risk by promoting insulin-glucose dysregulation, oxidative stress, hormonal imbalances, and excess adiposity. This prospective study investigates the association between dietary sugars(fructose and sucrose) and sugary foods and beverages in relation to combined and site-specific (breast, prostate, colorectal) adiposity-associated cancers. The analytic sample consisted of 3,184 adults, aged 26-84y, from the Framingham Offspring cohort. Diet data was first collected between 1991-1995 using a food frequency questionnaire. Intakes of fructose, sucrose, sugary foods and sugary beverages (fruit juice and sugar-sweetened beverages) were derived. Participants were followed up until 2013 to ascertain cancer incidence; 565 doctor-diagnosed adiposity-related cancers, including 124 breast, 157 prostate and 68 colorectal cancers occurred. Multivariable-adjusted Cox proportional hazards models were used to evaluate associations. Tests for interaction with BMI and waist circumference were conducted. No associations were observed between fructose, sucrose, sugary food consumption and combined incidence of adiposity-related cancers or the examined site-specific cancers. While total consumption of sugary beverages was not associated with site-specific cancer risk, higher intakes of fruit juice were associated with 58% increased prostate cancer risk(HR:1.58;95%CI:1.04-2.41) in multivariable-adjusted models. In exploratory stratified analyses, higher sugary beverage intakes increased overall adiposity-related cancer risk by 59% in participants with excessive central adiposity(HR:1.59;95%CI:1.01-2.50)(p-trend=0.057). In this cohort of American adults, higher sugary beverage consumption was associated with increased cancer risk among participants with central adiposity. These analyses suggest that avoiding sugary beverages represents a simple dietary modification that may be used as an effective cancer control strategy. Copyright ©2018

A model of pathways to artificial superintelligence catastrophe for risk and decision analysis

Science.gov (United States)

Barrett, Anthony M.; Baum, Seth D.

2017-03-01

An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.

Calibration plots for risk prediction models in the presence of competing risks.

Science.gov (United States)

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

2014-08-15

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems. Copyright © 2014 John Wiley & Sons, Ltd.

Affect and Acceptability: Exploring Teachers' Technology-Related Risk Perceptions

Science.gov (United States)

Howard, Sarah K.

2011-01-01

Educational change, such as technology integration, involves risk. Teachers are encouraged to "take risks", but what risks they are asked to take and how do they perceive these risks? Developing an understanding of teachers' technology-related risk perceptions can help explain their choices and behaviours. This paper presents a way to…

Optimal Consumption and Investment under Time-Varying Relative Risk Aversion

DEFF Research Database (Denmark)

Steffensen, Mogens

2011-01-01

We consider the continuous time consumption-investment problem originally formalized and solved by Merton in case of constant relative risk aversion. We present a complete solution for the case where relative risk aversion with respect to consumption varies with time, having in mind an investor...... with age-dependent risk aversion. This provides a new motivation for life-cycle investment rules. We study the optimal consumption and investment rules, in particular in the case where the relative risk aversion with respect to consumption is increasing with age....

Adolescent mental health and academic functioning: empirical support for contrasting models of risk and vulnerability.

Science.gov (United States)

Lucier-Greer, Mallory; O'Neal, Catherine W; Arnold, A Laura; Mancini, Jay A; Wickrama, Kandauda K A S

2014-11-01

Adolescents in military families contend with normative stressors that are universal and exist across social contexts (minority status, family disruptions, and social isolation) as well as stressors reflective of their military life context (e.g., parental deployment, school transitions, and living outside the United States). This study utilizes a social ecological perspective and a stress process lens to examine the relationship between multiple risk factors and relevant indicators of youth well-being, namely depressive symptoms and academic performance, as well as the mediating role of self-efficacy (N = 1,036). Three risk models were tested: an additive effects model (each risk factor uniquely influences outcomes), a full cumulative effects model (the collection of risk factors influences outcomes), a comparative model (a cumulative effects model exploring the differential effects of normative and military-related risks). This design allowed for the simultaneous examination of multiple risk factors and a comparison of alternative perspectives on measuring risk. Each model was predictive of depressive symptoms and academic performance through persistence; however, each model provides unique findings about the relationship between risk factors and youth outcomes. Discussion is provided pertinent to service providers and researchers on how risk is conceptualized and suggestions for identifying at-risk youth. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

Genetic instability model for cancer risk in A-bomb survivors

International Nuclear Information System (INIS)

Niwa, Ohtsura

1998-01-01

This review was written rather against Mendelsohn's reductionist model for cancer risk in A-bomb survivors in following chapters. Assumptions for carcinogenic process: mutation of a cell to the cancer cell and its proliferation. Multi-step theory for carcinogenesis and age of crisis: induction of cancer by accumulation of cancer-related gene mutations which being linear to time (age). Effect of exogenous hit in the multi-step theory: radiation as an exogenous hit to damage DNA. Dose-effect relationship for cancer risk in the survivors and the problem for the latent period: for solid tumors, dose-effect relationship is linear and shortening of the latent period is not observed. Considerations on cancer data in adulthood exposure/Indirect effect model in radiation carcinogenesis: solid cancer data supporting the indirect effect model. Possible mechanism for radiation-induced long-term increase of natural mutation frequency: genetic instability remaining in the irradiated cells which being a basis of the indirect effect model. Notes for considerations of carcinogenicity in exposed people/Difference in carcinogenic mechanisms due to age. The author concluded that the radiation-induced carcinogenesis is deeply related with the natural carcinogenesis and particularly for solid cancers, it can not be explained by the classic reductionist model. (K.H.)

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

Science.gov (United States)

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

The perils of picky eating: dietary breadth is related to extinction risk in insectivorous bats.

Directory of Open Access Journals (Sweden)

Justin G Boyles

2007-07-01

Full Text Available Several recent papers evaluate the relationship between ecological characteristics and extinction risk in bats. These studies report that extinction risk is negatively related to geographic range size and positively related to habitat specialization. Here, we evaluate the hypothesis that extinction risk is also related to dietary specialization in insectivorous vespertilionid bats using both traditional and phylogenetically-controlled analysis of variance. We collected dietary data and The World Conservation Union (IUCN rankings for 44 Australian, European, and North American bat species. Our results indicate that species of conservation concern (IUCN ranking near threatened or above are more likely to have a specialized diet than are species of least concern. Additional analyses show that dietary breadth is not correlated to geographic range size or wing morphology, characteristics previously found to correlate with extinction risk. Therefore, there is likely a direct relationship between dietary specialization and extinction risk; however, the large variation in dietary breadth within species of least concern suggests that diet alone cannot explain extinction risk. Our results may have important implications for the development of predictive models of extinction risk and for the assignment of extinction risk to insectivorous bat species. Similar analyses should be conducted on additional bat families to assess the generality of this relationship between niche breadth and extinction risk.

Elderly Taiwanese's Intrinsic Risk Factors for Fall-related Injuries

OpenAIRE

In-Fun Li; Yvonne Hsiung; Hui-Fen Hsing; Mei-Yu Lee; Te-Hsin Chang; Ming-Yuan Huang

2016-01-01

Background: As a vital issue in geriatric research, risk factors for falls were concluded to be multifactorial, and prevention has been mostly aimed at decreasing situational and environmental risks that cause and aggravate fall-related injuries, particularly within the institutions. While knowledge is limited about older patients' intrinsic determinants, the purpose of this study was to explore elderly Taiwanese's intrinsic risk factors associated with severe fall-related injuries. Method...

A risk prediction model for xerostomia: a retrospective cohort study.

Science.gov (United States)

Villa, Alessandro; Nordio, Francesco; Gohel, Anita

2016-12-01

We investigated the prevalence of xerostomia in dental patients and built a xerostomia risk prediction model by incorporating a wide range of risk factors. Socio-demographic data, past medical history, self-reported dry mouth and related symptoms were collected retrospectively from January 2010 to September 2013 for all new dental patients. A logistic regression framework was used to build a risk prediction model for xerostomia. External validation was performed using an independent data set to test the prediction power. A total of 12 682 patients were included in this analysis (54.3%, females). Xerostomia was reported by 12.2% of patients. The proportion of people reporting xerostomia was higher among those who were taking more medications (OR = 1.11, 95% CI = 1.08-1.13) or recreational drug users (OR = 1.4, 95% CI = 1.1-1.9). Rheumatic diseases (OR = 2.17, 95% CI = 1.88-2.51), psychiatric diseases (OR = 2.34, 95% CI = 2.05-2.68), eating disorders (OR = 2.28, 95% CI = 1.55-3.36) and radiotherapy (OR = 2.00, 95% CI = 1.43-2.80) were good predictors of xerostomia. For the test model performance, the ROC-AUC was 0.816 and in the external validation sample, the ROC-AUC was 0.799. The xerostomia risk prediction model had high accuracy and discriminated between high- and low-risk individuals. Clinicians could use this model to identify the classes of medications and systemic diseases associated with xerostomia. © 2015 John Wiley & Sons A/S and The Gerodontology Association. Published by John Wiley & Sons Ltd.

Oil spill risk assessment : relative impact indices by oil type and location

International Nuclear Information System (INIS)

French-McCay, D.; Beegle-Krause, C.J.; Rowe, J.; Rodriguez, W.; Schmidt Etkin, D.

2009-01-01

The aim of the study was to inform policies related to resource allocation for oil spill prevention, preparedness and response activities in Washington State. Oil spill reports and impact modelling studies were evaluated in order to determine major risk consequence factors including spill volume, location, timing, toxicity, persistence, and expected frequency of spills by sector. The Washington Compensation Schedule pre-assessment screening and oil spill compensation schedule regulations (WCS) designed to consider the sensitivity of oiled areas as well as the relative density and seasonal distributions of sensitive biota. Spill incidents were assigned per-gallon impact scores based on geographic location, oil type, and season. The WCS qualitative rating system was used to assess the potential impacts of spills in different geographic systems. Geographic zones were based on geography, circulation of currents, climate, and the WCS sub-regions in estuarine and marine areas on the Pacific coast of Washington State. Oil types included crude, heavy, and light oils; gasoline; jet fuel; and non-petroleum oils. A habitat index was calculated to represent existing stream conditions. It was concluded that the relative impact risk model is a reliable method for characterizing impacts based on spill volume, oil effects, and vulnerability rankings. 25 refs., 20 tabs., 3 figs

ISM Approach to Model Offshore Outsourcing Risks

Directory of Open Access Journals (Sweden)

Sunand Kumar

2014-07-01

Full Text Available In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain network. This also leads to dissatisfaction among different stake holders. The main objective of this paper is to identify and understand the mutual interaction among various risks which affect the performance of offshore outsourcing.  To this effect, authors have identified various risks through extant review of literature.  From this information, an integrated model using interpretive structural modelling (ISM for risks affecting offshore outsourcing is developed and the structural relationships between these risks are modeled.  Further, MICMAC analysis is done to analyze the driving power and dependency of risks which shall be helpful to managers to identify and classify important criterions and to reveal the direct and indirect effects of each criterion on offshore outsourcing. Results show that political risk and risk due to cultural differences are act as strong drivers.

THE ANALYSIS OF THE RELATION COUNTRY RISK – MULTIPLE VALUE

Directory of Open Access Journals (Sweden)

Cristina Nicolescu

2016-12-01

Full Text Available Financial theory state that high expected growth, low risk in the company’s sector and low interest rates will push multiples higher. In this respect the goal of the empirical work is to examine country risk-multiple value relation, for the companies from emerging and frontier markets such as Central and East European ones. Specific control variables have been included in the model as proxy for growth opportunities, profitability, capital structure, and asset utilization. Using panel data analysis for period 2010-2015 as well as other financial variables for a sample of Central and East European countries during 2010-2015. The results partially support financial theories, mainly the significance of country risk and debt ratio and reject the growth opportunities hypothesis.

Artificial Systems and Models for Risk Covering Operations

Directory of Open Access Journals (Sweden)

Laurenţiu Mihai Treapăt

2017-04-01

Full Text Available Mainly, this paper focuses on the roles of artificial intelligence based systems and especially on risk-covering operations. In this context, the paper comes with theoretical explanations on real-life based examples and applications. From a general perspective, the paper enriches its value with a wide discussion on the related subject. The paper aims to revise the volatilities’ estimation models and the correlations between the various time series and also by presenting the Risk Metrics methodology, as explained is a case study. The advantages that the VaR estimation offers, consist of its ability to quantitatively and numerically express the risk level of a portfolio, at a certain moment in time and also the risk of on open position (in titles, in FX, commodities or granted loans, belonging to an economic agent or even individual; hence, its role in a more efficient capital allocation, in the assumed risk delimitation, and also as a performance measurement instrument. In this paper and the study case that completes our work, we aim to prove how we can prevent considerable losses and even bankruptcies if VaR is known and applied accordingly. For this reason, the universities inRomaniashould include or increase their curricula with the study of the VaR model as an artificial intelligence tool. The simplicity of the presented case study, most probably, is the strongest argument of the current work because it can be understood also by the readers that are not necessarily very experienced in the risk management field.

What are the real risks of sport-related concussion, and are they modifiable?

Science.gov (United States)

Randolph, Christopher; Kirkwood, Michael W

2009-07-01

Over the past two decades, the management of sport-related concussion has been the topic of increased attention in the scientific literature and in the popular media. Despite a proliferation of competing guidelines for concussion management, the widespread use of neuropsychological "baseline" testing designed to monitor postinjury recovery, and several prospective controlled studies of the natural history of concussion, there has been virtually no attempt to quantify the risks associated with sport-related concussion or to determine whether these risks are modifiable via management strategies. Using American football as a model, the short- and long-term risks of sport-related concussion are reviewed. It is concluded that serious short-term consequences of sport-related concussion are extremely rare and unlikely to be significantly modified via management strategies that rely on baseline testing. Other less serious short-term adverse outcomes are also quite rare, transient, and not likely to be altered by specific management guidelines. The long-term consequences of multiple sport-related head trauma remain unclear but are potentially of greater public health concern and should be the focus of increased research. Based on available evidence, there is little rationale for the use of rigid strategies or guidelines in the place of individual clinical decision-making in the management of these injuries.

Public attitudes towards industrial, work-related and other risks

International Nuclear Information System (INIS)

Prescott-Clarke, P.

1982-01-01

Two reports describing work sponsored by the Health and Safety Executive are presented. The first describes a study of public attitudes towards industrial, work related, nuclear industry related and other risks. The second report describes public attitudes towards the acceptability of risks. (U.K.)

Brain tumour risk in relation to mobile telephone use

DEFF Research Database (Denmark)

Johansen, Christoffer

2010-01-01

The rapid increase in mobile telephone use has generated concern about possible health risks related to radiofrequency electromagnetic fields from this technology.......The rapid increase in mobile telephone use has generated concern about possible health risks related to radiofrequency electromagnetic fields from this technology....

Young people's perspectives on health-related risks

Directory of Open Access Journals (Sweden)

Grace Elisabeth Spencer

2008-07-01

Full Text Available Drawing upon current socio-cultural understandings of risk, this study highlights the disjunction between the expert risk discourses that permeate official public health policy and practice, and young people’s own perspectives on health and risk. Data were collected from young people aged 14-16 years through the use of group and individual interviews in a school and community youth centre setting. Findings from this study question the saliency of expert-defined health-related risks to young people’s everyday lives. Young people in this study saw health as closely linked to ‘being happy’. Friendships and a sense of personal achievement were particularly important to participants’ health and well-being. When accounting for their participation in health-related practices identified as ‘risky’ in government policy – such as smoking, alcohol and substance use – young people emphasised the levels of pressure they experienced. Sources of pressure included arguments and bullying, school work, and negative stereotypes of young people in general. These areas indicated young people’s concerns that reach beyond the official prescriptions permeating current health policy.

NGNP Risk Management Database: A Model for Managing Risk

International Nuclear Information System (INIS)

Collins, John

2009-01-01

To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft(reg s ign) Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool's design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

NGNP Risk Management Database: A Model for Managing Risk

Energy Technology Data Exchange (ETDEWEB)

John Collins

2009-09-01

To facilitate the implementation of the Risk Management Plan, the Next Generation Nuclear Plant (NGNP) Project has developed and employed an analytical software tool called the NGNP Risk Management System (RMS). A relational database developed in Microsoft® Access, the RMS provides conventional database utility including data maintenance, archiving, configuration control, and query ability. Additionally, the tool’s design provides a number of unique capabilities specifically designed to facilitate the development and execution of activities outlined in the Risk Management Plan. Specifically, the RMS provides the capability to establish the risk baseline, document and analyze the risk reduction plan, track the current risk reduction status, organize risks by reference configuration system, subsystem, and component (SSC) and Area, and increase the level of NGNP decision making.

Acute Myocardial Infarction Readmission Risk Prediction Models: A Systematic Review of Model Performance.

Science.gov (United States)

Smith, Lauren N; Makam, Anil N; Darden, Douglas; Mayo, Helen; Das, Sandeep R; Halm, Ethan A; Nguyen, Oanh Kieu

2018-01-01

Hospitals are subject to federal financial penalties for excessive 30-day hospital readmissions for acute myocardial infarction (AMI). Prospectively identifying patients hospitalized with AMI at high risk for readmission could help prevent 30-day readmissions by enabling targeted interventions. However, the performance of AMI-specific readmission risk prediction models is unknown. We systematically searched the published literature through March 2017 for studies of risk prediction models for 30-day hospital readmission among adults with AMI. We identified 11 studies of 18 unique risk prediction models across diverse settings primarily in the United States, of which 16 models were specific to AMI. The median overall observed all-cause 30-day readmission rate across studies was 16.3% (range, 10.6%-21.0%). Six models were based on administrative data; 4 on electronic health record data; 3 on clinical hospital data; and 5 on cardiac registry data. Models included 7 to 37 predictors, of which demographics, comorbidities, and utilization metrics were the most frequently included domains. Most models, including the Centers for Medicare and Medicaid Services AMI administrative model, had modest discrimination (median C statistic, 0.65; range, 0.53-0.79). Of the 16 reported AMI-specific models, only 8 models were assessed in a validation cohort, limiting generalizability. Observed risk-stratified readmission rates ranged from 3.0% among the lowest-risk individuals to 43.0% among the highest-risk individuals, suggesting good risk stratification across all models. Current AMI-specific readmission risk prediction models have modest predictive ability and uncertain generalizability given methodological limitations. No existing models provide actionable information in real time to enable early identification and risk-stratification of patients with AMI before hospital discharge, a functionality needed to optimize the potential effectiveness of readmission reduction interventions

Risk Modelling for Passages in Approach Channel

Directory of Open Access Journals (Sweden)

Leszek Smolarek

2013-01-01

Full Text Available Methods of multivariate statistics, stochastic processes, and simulation methods are used to identify and assess the risk measures. This paper presents the use of generalized linear models and Markov models to study risks to ships along the approach channel. These models combined with simulation testing are used to determine the time required for continuous monitoring of endangered objects or period at which the level of risk should be verified.

Varied definitions of risk related to sensation seeking trait

International Nuclear Information System (INIS)

Daastoel, P.Oe.U.; Drottz-Sjoeberg, B.M.

1999-01-01

This pilot study is based on the assumption and the knowledge that previous results show that the normal use of the word risk varies across subjects. The risk definitions the subjects use have also been shown to be related to various educational interests. A related field of research has developed measures for Sensation Seeking personality trait, with four facets. Three independent groups of first year psychology students reported their normal definition of the word risk using one of three measurement formats. The results showed, e.g. that the typical open-ended response to the personal definition of risk was danger. Subjects who defined risk as the combination of probability and consequences tended to score higher on the total Sensation Seeking Scale, as compared to those defining risk as the probability of an event

Varied definitions of risk related to sensation seeking trait

Energy Technology Data Exchange (ETDEWEB)

Daastoel, P.Oe.U.; Drottz-Sjoeberg, B.M. [Norwegian Univ. of Science and Technology, Trondheim (Norway). Dept. of Psychology

1999-12-01

This pilot study is based on the assumption and the knowledge that previous results show that the normal use of the word risk varies across subjects. The risk definitions the subjects use have also been shown to be related to various educational interests. A related field of research has developed measures for Sensation Seeking personality trait, with four facets. Three independent groups of first year psychology students reported their normal definition of the word risk using one of three measurement formats. The results showed, e.g. that the typical open-ended response to the personal definition of risk was danger. Subjects who defined risk as the combination of probability and consequences tended to score higher on the total Sensation Seeking Scale, as compared to those defining risk as the probability of an event.

Sexual HIV Risk Among Male Parolees and Their Female Partners: The Relate Project.

Science.gov (United States)

Comfort, Megan; Reznick, Olga Grinstead; Dilworth, Samantha E; Binson, Diane; Darbes, Lynae A; Neilands, Torsten B

The massively disproportionate impact of America's prison boom on communities of color has raised questions about how incarceration may affect health disparities, including disparities in HIV. Primary partners are an important source of influence on sexual health. In this paper, we investigate sexual HIV risk among male-female couples following a man's release from prison. We draw upon data from the Relate Project, a novel cross-sectional survey of recently released men and their female partners in Oakland and San Francisco, California (N=344). Inferential analyses use the actor-partner model to explore actor and partner effects on sexual HIV risk outcomes. Dyadic analyses of sexual HIV risk among male parolees and their female partners paint a complex portrait of couples affected by incarceration and of partners' influences on each other. Findings indicate that demographic factors such as education level and employment status, individual psycho-social factors such as perception of risk, and relationship factors such as commitment and power affect sexual HIV risk outcomes. The Relate Project provides a novel dataset for the dyadic analysis of sexual risk among male parolees and their female partners, and results highlight the importance of focusing on the couple as a unit when assessing HIV risk and protective behaviors. Results also indicate potentially fruitful avenues for population-specific interventions that may help to reduce sexual health disparities among couples affected by incarceration.

The air emissions risk assessment model (AERAM)

International Nuclear Information System (INIS)

Gratt, L.B.

1991-01-01

AERAM is an environmental analysis and power generation station investment decision support tool. AERAM calculates the public health risk (in terms of the lifetime cancers) in the nearby population from pollutants released into the air. AERAM consists of four main subroutines: Emissions, Air, Exposure and Risk. The Emission subroutine uses power plant parameters to calculate the expected release of the pollutants. A coal-fired and oil-fired power plant are currently available. A gas-fired plant model is under preparation. The release of the pollutants into the air is followed by their dispersal in the environment. The dispersion in the Air Subroutine uses the Environmental Protection Agency's model, Industrial Source Complex-Long Term. Additional dispersion models (Industrial Source Complex - Short Term and Cooling Tower Drift) are being implemented for future AERAM versions. The Expose Subroutine uses the ambient concentrations to compute population exposures for the pollutants of concern. The exposures are used with corresponding dose-response model in the Risk Subroutine to estimate both the total population risk and individual risk. The risk for the dispersion receptor-population centroid for the maximum concentration is also calculated for regulatory-population purposes. In addition, automated interfaces with AirTox (an air risk decision model) have been implemented to extend AERAM's steady-state single solution to the decision-under-uncertainty domain. AERAM was used for public health risks, the investment decision for additional pollution control systems based on health risk reductions, and the economics of fuel vs. health risk tradeoffs. AERAM provides that state-of-the-art capability for evaluating the public health impact airborne toxic substances in response to regulations and public concern

Application of a regional hurricane wind risk forecasting model for wood-frame houses.

Science.gov (United States)

Jain, Vineet Kumar; Davidson, Rachel Ann

2007-02-01

Hurricane wind risk in a region changes over time due to changes in the number, type, locations, vulnerability, and value of buildings. A model was developed to quantitatively estimate changes over time in hurricane wind risk to wood-frame houses (defined in terms of potential for direct economic loss), and to estimate how different factors, such as building code changes and population growth, contribute to that change. The model, which is implemented in a simulation, produces a probability distribution of direct economic losses for each census tract in the study region at each time step in the specified time horizon. By changing parameter values and rerunning the analysis, the effects of different changes in the built environment on the hurricane risk trends can be estimated and the relative effectiveness of hypothetical mitigation strategies can be evaluated. Using a case study application for wood-frame houses in selected counties in North Carolina from 2000 to 2020, this article demonstrates how the hurricane wind risk forecasting model can be used: (1) to provide insight into the dynamics of regional hurricane wind risk-the total change in risk over time and the relative contribution of different factors to that change, and (2) to support mitigation planning. Insights from the case study include, for example, that the many factors contributing to hurricane wind risk for wood-frame houses interact in a way that is difficult to predict a priori, and that in the case study, the reduction in hurricane losses due to vulnerability changes (e.g., building code changes) is approximately equal to the increase in losses due to building inventory growth. The potential for the model to support risk communication is also discussed.

Analytical Modeling for Underground Risk Assessment in Smart Cities

Directory of Open Access Journals (Sweden)

Israr Ullah

2018-06-01

Full Text Available In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a simple linear approximation based on multiple linear regression analysis; (b hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c hybrid approximation approach which is a combination of (a and (b. Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.

[Study on the infectious risk model of AIDS among men who have sex with men in Guangzhou].

Science.gov (United States)

Hu, Pei; Zhong, Fei; Cheng, Wei-Bin; Xu, Hui-Fang; Ling, Li

2012-07-01

To develop a human immune deficiency virus (HIV) infection risk appraisal model suitable for men who has sex with men (MSM) in Guangzhou, and to provide tools for follow-up the outcomes on health education and behavior intervention. A cros-sectional study was conducted in Guangzhou from 2008 to 2010. Based on the HIV surveillance data, the main risk factors of HIV infection among MSM were screened by means of logistic regression. Degree on relative risk was transformed into risk scores by adopting the statistics models. Individual risk scores, group risk scores and individual infection risk in comparison with usual MSM groups could then be calculated according to the rate of exposure on those risk factors appeared in data from the surveillance programs. Risk factors related to HIV infection among MSM and the quantitative assessment standard (risk scores and risk scores table of population groups) for those factors were set up by multiple logistic regression, including age, location of registered residence, monthly income, major location for finding their sexual partners, HIV testing in the past year, age when having the first sexual intercourse, rate of condom use in the past six months, symptoms related to sexually transmitted diseases (STDs) and syphilis in particular. The average risk score of population was 6.06, with risk scores for HIV positive and negative as 3.10 and 18.08 respectively (P risk model could be used to quantify and classify the individual's infectious status and related factors among MSM more directly and effectively, so as to help the individuals to identify their high-risk behaviors as well as lifestyles. We felt that it could also serve as an important tool used for personalized HIV health education and behavior intervention programs.

[Mother-newborn relational risk - Study of prevalence and associated variables].

Science.gov (United States)

Muñoz, Maribel; Poo, Ana María; Baeza, Bernardita; Bustos, M Luis

2015-01-01

Clinical evidence reveals the importance of mother-newborn bonding experience for health promoting and maintenance of human life. If the newborn lacks care and affection, she/he may develop an attachment disorder. A predictive scale regarding the risk of mothernewborn relationships is available, which makes possible an early intervention to prevent the development of relational disorders. The aim of this study is to apply the Kimelman measurement scale to determine the relational risk in mother-newborn pairs, as well as the prevalence and the associated biopsychosocial variables. A cross-sectional study with a probabilistic sample of 333 mother-infant pairs in postpartum maternity at Temuco hospital. The Kimelman mother-newborn attachment assessment guide was used. Biopsychosocial variables were obtained from the mothers studied. The association of biopsychosocial variables with relational risk was analyzed using OR and confidence intervals of 95%. The prevalence of high relational risk was 43.8%. The associated biopsychosocial variables included, women with no steady partner, single parent, teenage mothers, unwanted and unplanned pregnancy. Almost half of the mothers were in the high risk group. Early identification of relational risk and its related variables could help in the intervention in this vulnerable group. Copyright © 2015. Publicado por Elsevier España, S.L.U.

Reducing health risk in family members of patients with type 2 diabetes: views of first degree relatives

Directory of Open Access Journals (Sweden)

O'Sullivan Bernadette

2009-12-01

Full Text Available Abstract Background Patients with type 2 diabetes can have an important role in discussing health risk within families. This study aimed to establish the acceptability to first degree relatives towards their relative with type 2 diabetes intervening as health promoters in their own families, using the Health Belief Model as a theoretical framework for evaluation. Methods Cross-sectional questionnaire design. Survey questionnaire for first degree relative (sibling or child mailed to a random sample of patients with type 2 diabetes registered with an urban hospital diabetes clinic (n = 607 eligible patients. Patients were asked to pass on questionnaires to one to two first degree relatives. Results Questionnaires were returned from 257 families (42% response rate with two responses provided by 107 families (a total of 364 questionnaires. The majority (94% of first degree relatives of patients with type 2 diabetes would like to be informed about reducing their risk. Half (48% of respondents reported being spoken to by a relative with type 2 diabetes about their risk of diabetes. Those spoken to were more likely to see themselves at risk of diabetes, to worry about developing diabetes and to view diabetes as a serious condition. Conclusions A role for patients with type 2 diabetes in discussing health risk in their family appears to be acceptable to many relatives. Discussion of risk and interventions to reduce health risk with their relatives should be encouraged in patients with type 2 diabetes.

Reducing health risk in family members of patients with type 2 diabetes: views of first degree relatives.

LENUS (Irish Health Repository)

Whitford, David L

2009-01-01

BACKGROUND: Patients with type 2 diabetes can have an important role in discussing health risk within families. This study aimed to establish the acceptability to first degree relatives towards their relative with type 2 diabetes intervening as health promoters in their own families, using the Health Belief Model as a theoretical framework for evaluation. METHODS: Cross-sectional questionnaire design. Survey questionnaire for first degree relative (sibling or child) mailed to a random sample of patients with type 2 diabetes registered with an urban hospital diabetes clinic (n = 607 eligible patients). Patients were asked to pass on questionnaires to one to two first degree relatives. RESULTS: Questionnaires were returned from 257 families (42% response rate) with two responses provided by 107 families (a total of 364 questionnaires). The majority (94%) of first degree relatives of patients with type 2 diabetes would like to be informed about reducing their risk. Half (48%) of respondents reported being spoken to by a relative with type 2 diabetes about their risk of diabetes. Those spoken to were more likely to see themselves at risk of diabetes, to worry about developing diabetes and to view diabetes as a serious condition. CONCLUSIONS: A role for patients with type 2 diabetes in discussing health risk in their family appears to be acceptable to many relatives. Discussion of risk and interventions to reduce health risk with their relatives should be encouraged in patients with type 2 diabetes.

Calibration plots for risk prediction models in the presence of competing risks

DEFF Research Database (Denmark)

Gerds, Thomas A; Andersen, Per K; Kattan, Michael W

2014-01-01

A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks...... prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves...

Prostate Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Liver Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Colorectal Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Esophageal Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Bladder Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Lung Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Breast Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Pancreatic Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Ovarian Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Cervical Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Testicular Cancer Risk Prediction Models

Science.gov (United States)

Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Individualized Risk Model for Venous Thromboembolism After Total Joint Arthroplasty.

Science.gov (United States)

Parvizi, Javad; Huang, Ronald; Rezapoor, Maryam; Bagheri, Behrad; Maltenfort, Mitchell G

2016-09-01

Venous thromboembolism (VTE) after total joint arthroplasty (TJA) is a potentially fatal complication. Currently, a standard protocol for postoperative VTE prophylaxis is used that makes little distinction between patients at varying risks of VTE. We sought to develop a simple scoring system identifying patients at higher risk for VTE in whom more potent anticoagulation may need to be administered. Utilizing the National Inpatient Sample data, 1,721,806 patients undergoing TJA were identified, among whom 15,775 (0.9%) developed VTE after index arthroplasty. Among the cohort, all known potential risk factors for VTE were assessed. An initial logistic regression model using potential predictors for VTE was performed. Predictors with little contribution or poor predictive power were pruned from the data, and the model was refit. After pruning of variables that had little to no contribution to VTE risk, using the logistic regression, all independent predictors of VTE after TJA were identified in the data. Relative weights for each factor were determined. Hypercoagulability, metastatic cancer, stroke, sepsis, and chronic obstructive pulmonary disease had some of the highest points. Patients with any of these conditions had risk for postoperative VTE that exceeded the 3% rate. Based on the model, an iOS (iPhone operating system) application was developed (VTEstimator) that could be used to assign patients into low or high risk for VTE after TJA. We believe individualization of VTE prophylaxis after TJA can improve the efficacy of preventing VTE while minimizing untoward risks associated with the administration of anticoagulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Human Immunodeficiency Virus Related Knowledge, Risk ...

African Journals Online (AJOL)

There was poor HIV preventive practices; indicating ... Gyawali, et al.: HIV related knowledge, risk perception and practices among married women. Annals of Medical .... of this study correspond to the Indian, Nigerian and Iranian studies cited ...

A Knowledge-Based Model of Audit Risk

OpenAIRE

Dhar, Vasant; Lewis, Barry; Peters, James

1988-01-01

Within the academic and professional auditing communities, there has been growing concern about how to accurately assess the various risks associated with performing an audit. These risks are difficult to conceptualize in terms of numeric estimates. This article discusses the development of a prototype computational model (computer program) that assesses one of the major audit risks -- inherent risk. This program bases most of its inferencing activities on a qualitative model of a typical bus...

Modeling issues in nuclear plant fire risk analysis

International Nuclear Information System (INIS)

Siu, N.

1989-01-01

This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

Validation of a risk stratification tool for fall-related injury in a state-wide cohort.

Science.gov (United States)

McCoy, Thomas H; Castro, Victor M; Cagan, Andrew; Roberson, Ashlee M; Perlis, Roy H

2017-02-06

A major preventable contributor to healthcare costs among older individuals is fall-related injury. We sought to validate a tool to stratify such risk based on readily available clinical data, including projected medication adverse effects, using state-wide medical claims data. Sociodemographic and clinical features were drawn from health claims paid in the state of Massachusetts for individuals aged 35-65 with a hospital admission for a period spanning January-December 2012. Previously developed logistic regression models of hospital readmission for fall-related injury were refit in a testing set including a randomly selected 70% of individuals, and examined in a training set comprised of the remaining 30%. Medications at admission were summarised based on reported adverse effect frequencies in published medication labelling. The Massachusetts health system. A total of 68 764 hospitalised individuals aged 35-65 years. Hospital readmission for fall-related injury defined by claims code. A total of 2052 individuals (3.0%) were hospitalised for fall-related injury within 90 days of discharge, and 3391 (4.9%) within 180 days. After recalibrating the model in a training data set comprised of 48 136 individuals (70%), model discrimination in the remaining 30% test set yielded an area under the receiver operating characteristic curve (AUC) of 0.74 (95% CI 0.72 to 0.76). AUCs were similar across age decades (0.71 to 0.78) and sex (0.72 male, 0.76 female), and across most common diagnostic categories other than psychiatry. For individuals in the highest risk quartile, 11.4% experienced fall within 180 days versus 1.2% in the lowest risk quartile; 57.6% of falls occurred in the highest risk quartile. This analysis of state-wide claims data demonstrates the feasibility of predicting fall-related injury requiring hospitalisation using readily available sociodemographic and clinical details. This translatable approach to stratification allows for identification of

Credit Risk Evaluation : Modeling - Analysis - Management

OpenAIRE

Wehrspohn, Uwe

2002-01-01

An analysis and further development of the building blocks of modern credit risk management: -Definitions of default -Estimation of default probabilities -Exposures -Recovery Rates -Pricing -Concepts of portfolio dependence -Time horizons for risk calculations -Quantification of portfolio risk -Estimation of risk measures -Portfolio analysis and portfolio improvement -Evaluation and comparison of credit risk models -Analytic portfolio loss distributions The thesis contributes to the evaluatio...

Subcontractors and increased risk for work-related diseases and absenteeism.

Science.gov (United States)

Min, Kyoung B; Park, Shin G; Song, Jae S; Yi, Kwan H; Jang, Tae W; Min, Jin Y

2013-11-01

Despite increasing reliance on subcontracting in many economic sectors, there is little information available on occupational health and safety issues among subcontractor employees. The purpose of this study was to investigate the effect of subcontracting on self-reported health problems and absences due to occupational accidents and sickness using a nationally representative sample from South Korea. The data used were sampled from the second wave of the Korean Working Conditions Survey [2010]. Information on 3,282 parent firm employees and 728 subcontractor employees was obtained. For the logistic regression model, the outcomes were work-related health problems and absenteeism. The independent variables were personal and occupational characteristics, job aspects, and working hazards. Subcontractor employees were significantly more likely to experience health problems than the employee at parent firms. In particular, subcontractors' risk of injuries and anxiety/depression increased twofold (odd ratios, OR=2.01, 95% confidence interval, CIs, 1.24-3.26) and threefold (OR=2.95, 95% CIs 1.52-5.73), respectively, after controlling for potential variables. In addition, subcontractor employees were three times more likely than employees at parent firms to miss work due to illness (OR=3.56; 95% CIs 2.02-6.26). Working conditions, especially those related to job aspects and workplace exposures, attenuated these risks. Subcontracting workers were found to have a higher risk of work-related diseases and a higher absenteeism rate than parent firm workers. Our study highlights the need to protect and improve the occupational health and safety of subcontractor employees. Copyright © 2013 Wiley Periodicals, Inc.

Estimation of value at risk and conditional value at risk using normal mixture distributions model

Science.gov (United States)

Kamaruzzaman, Zetty Ain; Isa, Zaidi

2013-04-01

Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

Consideration on the health risk reduction related to attainment of the new particulate matter standards in Poland: A top-down policy risk assessment approach.

Science.gov (United States)

Kobza, Joanna; Pastuszka, Józef S; Gulis, Gabriel

2016-01-01

Policies can influence health of a population in various ways. Numerous epidemiological studies supported by toxicological investigations demonstrate a positive association between ambient concentrations of airborne particulate matter and increased adverse cardio-respiratory events, including morbidity and mortality. The aim of this paper was to present the concept of the top-down health policy risk assessment approach model developed to estimate the expected health risk reduction associated with policy aiming at attaining the new particulate matter ≤ 10 μm in diameter (PM10) standards in Poland. The top-down approach guides the analysis of causal chains from the policy to health outcomes. In this case study we tried to estimate the predicted health effects of the policy change over the past 20 years. Since Polish annual standard for PM10 changed from 50 μg/m³ in 1990 to 40 μg/m³ in 2010, we calculated the relative risk associated with decreasing PM10 in diameter to 10 μg/m3 in the annual level of PM10 for 6 adverse health effects. The relative risk slightly decreased for almost all adverse health effects, which means that the relative decrease in the incidence of health effects from the baseline incidence should range from about 0.5-0.6% for heart disease admissions to > 1% for respiratory admissions. The obtained results indicate that implementation of the new ambient air standards could influence improvement of the health status of Polish population. A top-down policy health risk assessment model can be one of the main tools in this process, providing harmonized guidance how to seek evidence-based information, which could serve policy-makers. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

Risk related behaviour under different ambient scent conditions

OpenAIRE

Alina Gagarina; Indre Pikturniene

2016-01-01

The article analyses the effect of two ambient scents (peppermint and vanilla) and their intensiveness on risk related behaviour that is expressed through selected decision making heuristics. Purpose of the article: The purpose of this article is to identify the relationship of ambient scent type and intensiveness with risk related behaviour that is expressed through selected decision making heuristics. Methodology/methods: 2×2 factorial experiment with control group was run. Ambi...

A comparative review of radiation-induced cancer risk models

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung Hee; Kim, Ju Youl [FNC Technology Co., Ltd., Yongin (Korea, Republic of); Han, Seok Jung [Risk and Environmental Safety Research Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2017-06-15

With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies. This review can be used as a basis for developing a Korean cancer risk model in the future.

Review on risk factors related to lower back disorders at workplace

Science.gov (United States)

A' Tifah Jaffar, Nur; Nasrull Abdol Rahman, Mohd

2017-08-01

This review examines the evidence of the occurrence of risk exposure on work-related lower back disorders in the workplace. This review also investigates potential interactions between the risk factors in the workplace which include heavy physical work risk factor, static work postures risk factor, frequent bending and twisting risk factor, lifting risk factor, pushing and pulling risk factor, repetitive work risk factor, vibration risk factor, psychological and psychosocial risk factor that may be associated with symptoms of musculoskeletal disorders of lower back. These risk factors can reinforce each other and their influence can also be mediated by cultural or social factors. A systematic review of the literature was carried out by searching using databases and the searching strategy was used combined keyword for risk factors, work-related lower back disorders, heavy physical work, static work postures, frequent bending and twisting, lifting, pushing and pulling, repetitive work, vibration, psychological and psychosocial risk factor. A total of 67 articles were identified and reviewed. The risk factors identified that related for low back disorder are seven which are heavy physical work, static work postures, frequent bending and twisting, lifting, pushing and pulling, repetitive work, vibration, psychological and psychosocial risk factor and the level of evidence supporting the relationship with lower back disorders also described such as strong, moderate, insufficient, limited and no evidence. This result confirms that, existing of higher physical and psychosocial demand related to reported risk factors of low back disorders. The result also showed that previous reviews had evaluated relationship between risk factors of low back disorders and specific types of musculoskeletal disorders. This review also highlights the scarves evidence regarding some of the frequently reported risk factors for work related lower back disorders.

Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

DEFF Research Database (Denmark)

Jonsdottir, Svava Osk; Reffstrup, Trine Klein; Petersen, Annette

2016-01-01

(ADME) of tebuconazole. The developed models were validated on in vivo half-life data for rabbit with good results, and on plasma and tissue concentration-time course data of tebuconazole after i.v. administration in rabbit. In most cases, the predicted concentration levels were seen to be within......A series of physiologically based toxicokinetic (PBTK) models for tebuconazole were developed in four species, rat, rabbit, rhesus monkey, and human. The developed models were analyzed with respect to the application of the models in higher tier human risk assessment, and the prospect of using...... such models in risk assessment of cumulative and aggregate exposure is discussed. Relatively simple and biologically sound models were developed using available experimental data as parameters for describing the physiology of the species, as well as the absorption, distribution, metabolism, and elimination...

Models as Relational Categories

Science.gov (United States)

Kokkonen, Tommi

2017-11-01

Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.

A Science for Citizenship Model: Assessing the Effects of Benefits, Risks, and Trust for Predicting Students' Interest in and Understanding of Science-Related Content

Science.gov (United States)

Jack, Brady Michael; Lee, Ling; Yang, Kuay-Keng; Lin, Huann-shyang

2017-10-01

This study showcases the Science for Citizenship Model (SCM) as a new instructional methodology for presenting, to secondary students, science-related technology content related to the use of science in society not taught in the science curriculum, and a new approach for assessing the intercorrelations among three independent variables (benefits, risks, and trust) to predict the dependent variable of triggered interest in learning science. Utilizing a 50-minute instructional presentation on nanotechnology for citizenship, data were collected from 301 Taiwanese high school students. Structural equation modeling (SEM) and paired-samples t-tests were used to analyze the fitness of data to SCM and the extent to which a 50-minute class presentation of nanotechnology for citizenship affected students' awareness of benefits, risks, trust, and triggered interest in learning science. Results of SCM on pre-tests and post-tests revealed acceptable model fit to data and demonstrated that the strongest predictor of students' triggered interest in nanotechnology was their trust in science. Paired-samples t-test results on students' understanding of nanotechnology and their self-evaluated awareness of the benefits and risks of nanotechology, trust in scientists, and interest in learning science revealed low significant differences between pre-test and post-test. These results provide evidence that a short 50-minute presentation on an emerging science not normally addressed within traditional science curriculum had a significant yet limited impact on students' learning of nanotechnology in the classroom. Finally, we suggest why the results of this study may be important to science education instruction and research for understanding how the integration into classroom science education of short presentations of cutting-edge science and emerging technologies in support of the science for citizenship enterprise might be accomplished through future investigations.

A model for the optimal risk management of (farm) firms

DEFF Research Database (Denmark)

Rasmussen, Svend

Current methods of risk management focus on efficiency and do not provide operational answers to the basic question of how to optimise and balance the two objectives, maximisation of expected income and minimisation of risk. This paper uses the Capital Asset Pricing Model (CAPM) to derive...... an operational criterion for the optimal risk management of firms. The criterion assumes that the objective of the firm manager is to maximise the market value of the firm and is based on the condition that the application of risk management tools has a symmetric effect on the variability of income around...... the mean. The criterion is based on the expected consequences of risk management on relative changes in the variance of return on equity and expected income. The paper demonstrates how the criterion may be used to evaluate and compare the effect of different risk management tools, and it illustrates how...

Risk Management Technologies With Logic and Probabilistic Models

CERN Document Server

Solozhentsev, E D

2012-01-01

This book presents intellectual, innovative, information technologies (I3-technologies) based on logical and probabilistic (LP) risk models. The technologies presented here consider such models for structurally complex systems and processes with logical links and with random events in economics and technology.  The volume describes the following components of risk management technologies: LP-calculus; classes of LP-models of risk and efficiency; procedures for different classes; special software for different classes; examples of applications; methods for the estimation of probabilities of events based on expert information. Also described are a variety of training courses in these topics. The classes of risk models treated here are: LP-modeling, LP-classification, LP-efficiency, and LP-forecasting. Particular attention is paid to LP-models of risk of failure to resolve difficult economic and technical problems. Amongst the  discussed  procedures of I3-technologies  are the construction of  LP-models,...

Cancer-related fatigue--mechanisms, risk factors, and treatments.

Science.gov (United States)

Bower, Julienne E

2014-10-01

Fatigue is one of the most common adverse effects of cancer that might persist for years after treatment completion in otherwise healthy survivors. Cancer-related fatigue causes disruption in all aspects of quality of life and might be a risk factor of reduced survival. The prevalence and course of fatigue in patients with cancer have been well characterized and there is growing understanding of the underlying biological mechanisms. Inflammation seems to have a key role in fatigue before, during, and after cancer-treatment. However, there is a considerable variability in the presentation of cancer-related fatigue, much of which is not explained by disease-related or treatment-related characteristics, suggesting that host factors might be important in the development and persistence of this symptom. Indeed, longitudinal studies have identified genetic, biological, psychosocial, and behavioural risk factors associated with cancer-related fatigue. Although no current gold-standard treatment for fatigue is available, a variety of intervention approaches have shown beneficial effects in randomized controlled trials, including physical activity, psychosocial, mind-body, and pharmacological treatments. This Review describes the mechanisms, risk factors, and possible interventions for cancer-related fatigue, focusing on recent longitudinal studies and randomized trials that have targeted fatigued patients.

Model-based mitigation of availability risks

NARCIS (Netherlands)

Zambon, E.; Bolzoni, D.; Etalle, S.; Salvato, M.

2007-01-01

The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for risk assessment and mitigation show limitations when evaluating and mitigating availability risks. This is due

Model-Based Mitigation of Availability Risks

NARCIS (Netherlands)

Zambon, Emmanuele; Bolzoni, D.; Etalle, Sandro; Salvato, Marco

2007-01-01

The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for Risk Assessment and Mitigation show limitations when evaluating and mitigating availability risks. This is due

Waterborne disease-related risk perceptions in the Sonora River basin, Mexico.

Science.gov (United States)

Morua, Agustin Robles; Halvorsen, Kathleen E; Mayer, Alex S

2011-05-01

Waterborne disease is estimated to cause about 10% of all diseases worldwide. However, related risk perceptions are not well understood, particularly in the developing world where waterborne disease is an enormous problem. We focus on understanding risk perceptions related to these issues in a region within northern Mexico. Our findings show how waterborne disease problems and solutions are understood in eight small communities along a highly contaminated river system. We found major differences in risk perceptions between health professionals, government officials, and lay citizens. Health professionals believed that a high level of human-waste-related risk existed within the region. Few officials and lay citizens shared this belief. In addition, few officials and lay citizens were aware of poor wastewater-management-related disease outbreaks and water contamination. Finally, aside from health professionals, a few interviewees understood the importance of basic hygiene and water treatment measures that could help to prevent disease. Our results add to the literature on environmentally-related risk perceptions in the developing world. We discuss recommendations for improving future human-wastewater-related risk communication within the region. © 2011 Society for Risk Analysis.

Civil engineering airman at increased risk for injuries and injury-related musculoskeletal disorders.

Science.gov (United States)

Webb, Timothy S; Wells, Timothy S

2011-03-01

With the advent of electronic records, the opportunity to conduct research on workplace-related injuries and musculoskeletal disorders has increased dramatically. The purpose of this study was to examine the United States Air Force Civil Engineering career field to determine if they are negatively impacted by their work environment. Specifically, the objective of this study was to determine if enlisted Civil Engineering Airmen (n = 25,385) were at increased risk for injury or injury-related musculoskeletal disorders compared to enlisted Information Management/Communications Airmen (n = 28,947). Using an historical prospective design, electronic data were assembled and analyzed using Cox's proportional hazards modeling. Models were stratified by gender and adjusted for race/ethnicity, marital status, birth year, and deployment status. Male Civil Engineers were observed to be at greater risk for both inpatient injury-related musculoskeletal disorders (HR = 1.86; 95% CI = 1.54-2.26) and injuries (HR = 1.77; 95% CI = 1.48-2.11), while female Civil Engineers were more than double the risk for both inpatient injury-related musculoskeletal disorders (HR = 2.18; 95% CI = 1.28-3.73) and injuries (HR = 2.22; 95% CI = 1.27-3.88) compared to Information Management/Communications Airmen. Although analyses do not allow exploration of specific causes, they highlight the utility of using electronic data to identify occupations for further evaluation. Based on these results, additional resources were allocated to survey Civil Engineers on their physical work demands and job requirements to identify key problem areas for further study and mitigation. Copyright © 2010 Wiley-Liss, Inc.

Building a risk-targeted regional seismic hazard model for South-East Asia

Science.gov (United States)

Woessner, J.; Nyst, M.; Seyhan, E.

2015-12-01

The last decade has tragically shown the social and economic vulnerability of countries in South-East Asia to earthquake hazard and risk. While many disaster mitigation programs and initiatives to improve societal earthquake resilience are under way with the focus on saving lives and livelihoods, the risk management sector is challenged to develop appropriate models to cope with the economic consequences and impact on the insurance business. We present the source model and ground motions model components suitable for a South-East Asia earthquake risk model covering Indonesia, Malaysia, the Philippines and Indochine countries. The source model builds upon refined modelling approaches to characterize 1) seismic activity from geologic and geodetic data on crustal faults and 2) along the interface of subduction zones and within the slabs and 3) earthquakes not occurring on mapped fault structures. We elaborate on building a self-consistent rate model for the hazardous crustal fault systems (e.g. Sumatra fault zone, Philippine fault zone) as well as the subduction zones, showcase some characteristics and sensitivities due to existing uncertainties in the rate and hazard space using a well selected suite of ground motion prediction equations. Finally, we analyze the source model by quantifying the contribution by source type (e.g., subduction zone, crustal fault) to typical risk metrics (e.g.,return period losses, average annual loss) and reviewing their relative impact on various lines of businesses.

A semi-quantitative model for risk appreciation and risk weighing

DEFF Research Database (Denmark)

Bos, Peter M.J.; Boon, Polly E.; van der Voet, Hilko

2009-01-01

Risk managers need detailed information on (1) the type of effect, (2) the size (severity) of the expected effect(s) and (3) the fraction of the population at risk to decide on well-balanced risk reduction measures. A previously developed integrated probabilistic risk assessment (IPRA) model...... provides quantitative information on these three parameters. A semi-quantitative tool is presented that combines information on these parameters into easy-readable charts that will facilitate risk evaluations of exposure situations and decisions on risk reduction measures. This tool is based on a concept...... detailed information on the estimated health impact in a given exposure situation. These graphs will facilitate the discussions on appropriate risk reduction measures to be taken....

Assessing flood risk at the global scale: model setup, results, and sensitivity

International Nuclear Information System (INIS)

Ward, Philip J; Jongman, Brenden; Weiland, Frederiek Sperna; Winsemius, Hessel C; Bouwman, Arno; Ligtvoet, Willem; Van Beek, Rens; Bierkens, Marc F P

2013-01-01

Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures. (letter)

Risk sharing relations and enforcement mechanisms

NARCIS (Netherlands)

Barr, A.; Dekker, M.; Fafchamps, M.

2008-01-01

We investigate whether the set of available enforcement mechanisms affects the formation of risk sharing relations by applying dyadic regression analysis to data from a specifically designed behavioural experiment, two surveys and a genealogical mapping exercise. During the experiment participants

The Relationship between Musculoskeletal Symptoms and Work-related Risk Factors in Hotel Workers.

Science.gov (United States)

Lee, Jin Woo; Lee, Ju Jong; Mun, Hyeon Je; Lee, Kyung-Jae; Kim, Joo Ja

2013-10-11

To identify work-related musculoskeletal symptoms and any associated work-related risk factors, focusing on structural labor factors among hotel workers. A total of 1,016 hotel workers (620 men and 396 women) were analyzed. The questionnaire surveyed participants' socio-demographics, health-related behaviors, job-related factors, and work-related musculoskeletal symptoms. Work-related musculoskeletal symptoms were assessed using the Nordic musculoskeletal questionnaire. All analyses were stratified by gender, and multiple logistic regression modeling was used to determine associations between work-related musculoskeletal symptoms and work-related risk factors. The risk of developing work-related musculoskeletal symptoms was 1.9 times higher among male workers in the kitchen department than males in the room department (OR = 1.92, 95% CI = 1.03-3.79), and 2.5 times higher among male workers with lower sleep satisfaction than those with higher sleep satisfaction (OR = 2.52, 95% CI = 1.57-4.04). All of the aforementioned cases demonstrated a statistically significant association with work-related musculoskeletal symptoms. Moreover, the risk of developing work-related musculoskeletal symptoms was 3.3 times higher among female workers aged between 30 and 34 than those aged 24 or younger (OR = 3.32, 95% CI = 1.56-7.04); 0.3 times higher among females in the back office department than those in the room department (OR = 0.34, 95% CI = 0.12-0.91); 1.6 times higher among females on shift schedules than those who were not (OR = 1.60, 95% CI = 1.02-2.59); 1.8 times higher among females who performed more intensive work than those who performed less intensive work (OR = 1.88, 95% CI = 1.17-3.02), and; 2.1 times higher among females with lower sleep satisfaction than those with higher sleep satisfaction (OR = 2.17, 95% CI = 1.34-3.50). All of the aforementioned cases also displayed a statistically significant association with work-related musculoskeletal symptoms. This study

A Corrosion Risk Assessment Model for Underground Piping

Science.gov (United States)

Datta, Koushik; Fraser, Douglas R.

2009-01-01

The Pressure Systems Manager at NASA Ames Research Center (ARC) has embarked on a project to collect data and develop risk assessment models to support risk-informed decision making regarding future inspections of underground pipes at ARC. This paper shows progress in one area of this project - a corrosion risk assessment model for the underground high-pressure air distribution piping system at ARC. It consists of a Corrosion Model of pipe-segments, a Pipe Wrap Protection Model; and a Pipe Stress Model for a pipe segment. A Monte Carlo simulation of the combined models provides a distribution of the failure probabilities. Sensitivity study results show that the model uncertainty, or lack of knowledge, is the dominant contributor to the calculated unreliability of the underground piping system. As a result, the Pressure Systems Manager may consider investing resources specifically focused on reducing these uncertainties. Future work includes completing the data collection effort for the existing ground based pressure systems and applying the risk models to risk-based inspection strategies of the underground pipes at ARC.

Development and Validation of a Prediction Model to Estimate Individual Risk of Pancreatic Cancer.

Science.gov (United States)

Yu, Ami; Woo, Sang Myung; Joo, Jungnam; Yang, Hye-Ryung; Lee, Woo Jin; Park, Sang-Jae; Nam, Byung-Ho

2016-01-01

There is no reliable screening tool to identify people with high risk of developing pancreatic cancer even though pancreatic cancer represents the fifth-leading cause of cancer-related death in Korea. The goal of this study was to develop an individualized risk prediction model that can be used to screen for asymptomatic pancreatic cancer in Korean men and women. Gender-specific risk prediction models for pancreatic cancer were developed using the Cox proportional hazards model based on an 8-year follow-up of a cohort study of 1,289,933 men and 557,701 women in Korea who had biennial examinations in 1996-1997. The performance of the models was evaluated with respect to their discrimination and calibration ability based on the C-statistic and Hosmer-Lemeshow type χ2 statistic. A total of 1,634 (0.13%) men and 561 (0.10%) women were newly diagnosed with pancreatic cancer. Age, height, BMI, fasting glucose, urine glucose, smoking, and age at smoking initiation were included in the risk prediction model for men. Height, BMI, fasting glucose, urine glucose, smoking, and drinking habit were included in the risk prediction model for women. Smoking was the most significant risk factor for developing pancreatic cancer in both men and women. The risk prediction model exhibited good discrimination and calibration ability, and in external validation it had excellent prediction ability. Gender-specific risk prediction models for pancreatic cancer were developed and validated for the first time. The prediction models will be a useful tool for detecting high-risk individuals who may benefit from increased surveillance for pancreatic cancer.

The System Cost Model: A tool for life cycle cost and risk analysis

International Nuclear Information System (INIS)

Hsu, K.; Lundeen, A.; Shropshire, D.; Sherick, M.

1996-01-01

In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors began development of the System Cost Model (SCM) application. The SCM estimates life cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, and transuranic waste. The SCM uses parametric cost functions to estimate life cycle costs for various treatment, storage, and disposal modules which reflect planned and existing waste management facilities at DOE installations. In addition, SCM can model new TSD facilities based on capacity needs over the program life cycle. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction, operations and maintenance, and decommissioning these waste management facilities. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. A complement to the SCM is the System Cost Model-Risk (SCM-R) model, which provides relative Environmental, Safety, and Health (ES and H) risk information. A relative ES and H risk basis has been developed and applied by LITCO at the INEL. The risk basis is now being automated in the SCM-R to facilitate rapid risk analysis of system alternatives. The added risk functionality will allow combined cost and risk evaluation of EM alternatives

The relevance of socio-demographic and occupational variables for the assessment of work-related stress risk.

Science.gov (United States)

Marinaccio, Alessandro; Ferrante, Pierpaolo; Corfiati, Marisa; Di Tecco, Cristina; Rondinone, Bruna M; Bonafede, Michela; Ronchetti, Matteo; Persechino, Benedetta; Iavicoli, Sergio

2013-12-10

Work-related stress is widely recognized as one of the major challenges to occupational health and safety. The correlation between work-related stress risk factors and physical health outcomes is widely acknowledged. This study investigated socio-demographic and occupational variables involved in perceived risk of work-related stress. The Italian version of the Health and Safety Executive Management Standards Indicator Tool was used in a large survey to examine the relationship between work-related stress risks and workers' demographic and occupational characteristics. Out of 8,527 questionnaires distributed among workers (from 75 organizations) 6,378 were returned compiled (74.8%); a set of mixed effects models were adopted to test single and combined effects of the variables on work-related stress risk. Female workers reported lower scores on control and peer support and more negative perceptions of relationships and change at work than male workers, most of them with full-time contracts. Age, job seniority, and educational level appeared positively correlated with control at work, but negatively with job demands. Fixed-term workers had positive perceptions regarding job demands and relationships, but more difficulties about their role at work than permanent workers. A commuting time longer than one hour and shift work appeared to be associated with higher levels of risk factors for work-related stress (except for role), the latter having more negative effects, increasing with age. The findings suggest that the assessment and management of work-related stress risk should consider specific socio-demographic and occupational risk factors such as gender, age, educational level, job status, shift work, commuting time, job contracts.

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

Science.gov (United States)

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Discrete competing risk model with application to modeling bus-motor failure data

International Nuclear Information System (INIS)

Jiang, R.

2010-01-01

Failure data are often modeled using continuous distributions. However, a discrete distribution can be appropriate for modeling interval or grouped data. When failure data come from a complex system, a simple discrete model can be inappropriate for modeling such data. This paper presents two types of discrete distributions. One is formed by exponentiating an underlying distribution, and the other is a two-fold competing risk model. The paper focuses on two special distributions: (a) exponentiated Poisson distribution and (b) competing risk model involving a geometric distribution and an exponentiated Poisson distribution. The competing risk model has a decreasing-followed-by-unimodal mass function and a bathtub-shaped failure rate. Five classical data sets on bus-motor failures can be simultaneously and appropriately fitted by a general 5-parameter competing risk model with the parameters being functions of the number of successive failures. The lifetime and aging characteristics of the fitted distribution are analyzed.

Autoantibodies to IA-2beta improve diabetes risk assessment in high-risk relatives

DEFF Research Database (Denmark)

Achenbach, P; Bonifacio, E; Williams, A J K

2008-01-01

-positive participants (median age 12.1 years; 57% male), 113 developed diabetes (5 year cumulative risk 56%), and 148 were also GADA-positive and IAA-positive (4Ab-positive). IA2betaA were detected in 137 (65%) ICA/IA2A-positive participants and were associated with an increased 5 year diabetes risk (IA2beta......A-positive 65 vs 39% in IA2betaA-negative, p=0.0002). The effect was most marked in 4Ab-positive relatives (72% vs 52%, p=0.003). Metabolic testing further refined risk assessment. Among 101 4Ab-positive relatives with IA2betaA, the 5 year risk was 94% in those with a low FPIR (vs 50% in those with a normal...... FPIR, p4Ab/IA2betaA-positive participants with a low FPIR was 1.5 years. Multivariate analysis confirmed IA2betaA status, antibody number, young...

Risk matrix model for rotating equipment

Directory of Open Access Journals (Sweden)

Wassan Rano Khan

2014-07-01

Full Text Available Different industries have various residual risk levels for their rotating equipment. Accordingly the occurrence rate of the failures and associated failure consequences categories are different. Thus, a generalized risk matrix model is developed in this study which can fit various available risk matrix standards. This generalized risk matrix will be helpful to develop new risk matrix, to fit the required risk assessment scenario for rotating equipment. Power generation system was taken as case study. It was observed that eight subsystems were under risk. Only vibration monitor system was under high risk category, while remaining seven subsystems were under serious and medium risk categories.

Company Risk-related Disclosures in a Code Law Country: A Synopsis

Directory of Open Access Journals (Sweden)

Jonas Oliveira

2013-03-01

Full Text Available This synopsis provides a concise historical contextualisation of current risk disclosure issues, highlights major factors influencing contemporary risk reporting practices, and engages in a reflective overview of four recently published papers on aspects of corporate risk-related disclosures in a code law country, Portugal. The breadthand depth of our analysis is modest. Nonetheless we report findings indicating that risk-related disclosures are inadequate, lack transparency, and compound the difficulty of assessing the risk profile of a company. We contend that recent regulation initiatives have been of dubious effectiveness in improving the quality of riskinformation disclosed. In respect of the Portuguese context, we find that companies disclose risk-related information principally to reduce agency costs and to enhance corporate reputation. We contend that enhanced corporate accountability would be more likely to ensue if further disclosures of relevant risk-related information were mandated. One mechanism to do so would be through regulations recommended by the International Integrated Reporting Committee (IIRC.

A flexible Bayesian hierarchical model of preterm birth risk among US Hispanic subgroups in relation to maternal nativity and education.

Science.gov (United States)

Kaufman, Jay S; MacLehose, Richard F; Torrone, Elizabeth A; Savitz, David A

2011-04-19

Previous research has documented heterogeneity in the effects of maternal education on adverse birth outcomes by nativity and Hispanic subgroup in the United States. In this article, we considered the risk of preterm birth (PTB) using 9 years of vital statistics birth data from New York City. We employed finer categorizations of exposure than used previously and estimated the risk dose-response across the range of education by nativity and ethnicity. Using Bayesian random effects logistic regression models with restricted quadratic spline terms for years of completed maternal education, we calculated and plotted the estimated posterior probabilities of PTB (gestational age education by ethnic and nativity subgroups adjusted for only maternal age, as well as with more extensive covariate adjustments. We then estimated the posterior risk difference between native and foreign born mothers by ethnicity over the continuous range of education exposures. The risk of PTB varied substantially by education, nativity and ethnicity. Native born groups showed higher absolute risk of PTB and declining risk associated with higher levels of education beyond about 10 years, as did foreign-born Puerto Ricans. For most other foreign born groups, however, risk of PTB was flatter across the education range. For Mexicans, Central Americans, Dominicans, South Americans and "Others", the protective effect of foreign birth diminished progressively across the educational range. Only for Puerto Ricans was there no nativity advantage for the foreign born, although small numbers of foreign born Cubans limited precision of estimates for that group. Using flexible Bayesian regression models with random effects allowed us to estimate absolute risks without strong modeling assumptions. Risk comparisons for any sub-groups at any exposure level were simple to calculate. Shrinkage of posterior estimates through the use of random effects allowed for finer categorization of exposures without

Credit Risk Analysis Using Machine and Deep Learning Models

Directory of Open Access Journals (Sweden)

Peter Martey Addo

2018-04-01

Full Text Available Due to the advanced technology associated with Big Data, data availability and computing power, most banks or lending institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision-making and transparency. In this work, we build binary classifiers based on machine and deep learning models on real data in predicting loan default probability. The top 10 important features from these models are selected and then used in the modeling process to test the stability of binary classifiers by comparing their performance on separate data. We observe that the tree-based models are more stable than the models based on multilayer artificial neural networks. This opens several questions relative to the intensive use of deep learning systems in enterprises.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

Science.gov (United States)

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

Competing Risks and Multistate Models with R

CERN Document Server

Beyersmann, Jan; Schumacher, Martin

2012-01-01

This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

Modeling Research Project Risks with Fuzzy Maps

Science.gov (United States)

Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

2009-01-01

The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

Applying the welfare model to at-own-risk discharges.

Science.gov (United States)

Krishna, Lalit Kumar Radha; Menon, Sumytra; Kanesvaran, Ravindran

2017-08-01

"At-own-risk discharges" or "self-discharges" evidences an irretrievable breakdown in the patient-clinician relationship when patients leave care facilities before completion of medical treatment and against medical advice. Dissolution of the therapeutic relationship terminates the physician's duty of care and professional liability with respect to care of the patient. Acquiescence of an at-own-risk discharge by the clinician is seen as respecting patient autonomy. The validity of such requests pivot on the assumptions that the patient is fully informed and competent to invoke an at-own-risk discharge and that care up to the point of the at-own-risk discharge meets prevailing clinical standards. Palliative care's use of a multidisciplinary team approach challenges both these assumptions. First by establishing multiple independent therapeutic relations between professionals in the multidisciplinary team and the patient who persists despite an at-own-risk discharge. These enduring therapeutic relationships negate the suggestion that no duty of care is owed the patient. Second, the continued employ of collusion, familial determinations, and the circumnavigation of direct patient involvement in family-centric societies compromises the patient's decision-making capacity and raises questions as to the patient's decision-making capacity and their ability to assume responsibility for the repercussions of invoking an at-own-risk discharge. With the validity of at-own-risk discharge request in question and the welfare and patient interest at stake, an alternative approach to assessing at-own-risk discharge requests are called for. The welfare model circumnavigates these concerns and preserves the patient's welfare through the employ of a multidisciplinary team guided holistic appraisal of the patient's specific situation that is informed by clinical and institutional standards and evidenced-based practice. The welfare model provides a robust decision-making framework for

Potential Mediating Pathways through Which Sports Participation Relates to Reduced Risk of Suicidal Ideation

Science.gov (United States)

Taliaferro, Lindsay A.; Rienzo, Barbara A.; Miller, M. David; Pigg, R. Morgan; Dodd, Virginia J.

2010-01-01

Suicide ranks as the third leading cause of death for American youth. Researchers examining sport participation and suicidal behavior have regularly found inverse relationships. This study represents the first effort to test a model depicting potential mechanisms through which sport participation relates to reduced risk of suicidal ideation. The…

RELATIVE PROLIFERATION RISKS FOR NUCLEAR FUEL LEASING ARRANGEMENT

International Nuclear Information System (INIS)

CHENG, L.Y.; YUE, M.; BARI, R.A.

2007-01-01

The present study demonstrates a probabilistic approach to quantify the proliferation risks of fuel leasing and recycling. A Markov model approach is applied to evaluate the probability of proliferation success by diversion or theft. Proliferation risk is calculated as a product of the probability of success and the corresponding consequences

Relative risk analysis of several manufactured nanomaterials: an insurance industry context.

Science.gov (United States)

Robichaud, Christine Ogilvie; Tanzil, Dicksen; Weilenmann, Ulrich; Wiesner, Mark R

2005-11-15

A relative risk assessment is presented for the industrial fabrication of several nanomaterials. The production processes for five nanomaterials were selected for this analysis, based on their current or near-term potential for large-scale production and commercialization: single-walled carbon nanotubes, bucky balls (C60), one variety of quantum dots, alumoxane nanoparticles, and nano-titanium dioxide. The assessment focused on the activities surrounding the fabrication of nanomaterials, exclusive of any impacts or risks with the nanomaterials themselves. A representative synthesis method was selected for each nanomaterial based on its potential for scaleup. A list of input materials, output materials, and waste streams for each step of fabrication was developed and entered into a database that included key process characteristics such as temperature and pressure. The physical-chemical properties and quantities of the inventoried materials were used to assess relative risk based on factors such as volatility, carcinogenicity, flammability, toxicity, and persistence. These factors were first used to qualitatively rank risk, then combined using an actuarial protocol developed by the insurance industry for the purpose of calculating insurance premiums for chemical manufacturers. This protocol ranks three categories of risk relative to a 100 point scale (where 100 represents maximum risk): incident risk, normal operations risk, and latent contamination risk. Results from this analysis determined that relative environmental risk from manufacturing each of these five materials was comparatively low in relation to other common industrial manufacturing processes.

Why operational risk modelling creates inverse incentives

NARCIS (Netherlands)

Doff, R.

2015-01-01

Operational risk modelling has become commonplace in large international banks and is gaining popularity in the insurance industry as well. This is partly due to financial regulation (Basel II, Solvency II). This article argues that operational risk modelling is fundamentally flawed, despite efforts

Hair 2010 Documentation: Calculating risk indicators related to agricultural use of pesticides within the European Union

NARCIS (Netherlands)

Kruijne, R.; Deneer, J.W.; Lahr, J.; Vlaming, J.

2011-01-01

The HAIR instrument calculates risk indicators related to the agricultural use of pesticides in EU Member States. HAIR combines databases and models for calculating potential environmental environmental effects expressed by the exposure toxicity ratio.

Operational risk quantification and modelling within Romanian insurance industry

Directory of Open Access Journals (Sweden)

Tudor Răzvan

2017-07-01

Full Text Available This paper aims at covering and describing the shortcomings of various models used to quantify and model the operational risk within insurance industry with a particular focus on Romanian specific regulation: Norm 6/2015 concerning the operational risk issued by IT systems. While most of the local insurers are focusing on implementing the standard model to compute the Operational Risk solvency capital required, the local regulator has issued a local norm that requires to identify and assess the IT based operational risks from an ISO 27001 perspective. The challenges raised by the correlations assumed in the Standard model are substantially increased by this new regulation that requires only the identification and quantification of the IT operational risks. The solvency capital requirement stipulated by the implementation of Solvency II doesn’t recommend a model or formula on how to integrate the newly identified risks in the Operational Risk capital requirements. In this context we are going to assess the academic and practitioner’s understanding in what concerns: The Frequency-Severity approach, Bayesian estimation techniques, Scenario Analysis and Risk Accounting based on risk units, and how they could support the modelling of operational risk that are IT based. Developing an internal model only for the operational risk capital requirement proved to be, so far, costly and not necessarily beneficial for the local insurers. As the IT component will play a key role in the future of the insurance industry, the result of this analysis will provide a specific approach in operational risk modelling that can be implemented in the context of Solvency II, in a particular situation when (internal or external operational risk databases are scarce or not available.

[The application of two occupation health risk assessment models in a wooden furniture manufacturing industry].

Science.gov (United States)

Wang, A H; Leng, P B; Bian, G L; Li, X H; Mao, G C; Zhang, M B

2016-10-20

Objective: To explore the applicability of 2 different models of occupational health risk assessment in wooden furniture manufacturing industry. Methods: American EPA inhalation risk model and ICMM model of occupational health risk assessment were conducted to assess occupational health risk in a small wooden furniture enterprises, respectively. Results: There was poor protective measure and equipment of occupational disease in the plant. The concentration of wood dust in the air of two workshops was over occupational exposure limit (OEL) , and the C TWA was 8.9 mg/m 3 and 3.6 mg/m 3 , respectively. According to EPA model, the workers who exposed to benzene in this plant had high risk (9.7×10 -6 ~34.3×10 -6 ) of leukemia, and who exposed to formaldehyde had high risk (11.4 × 10 -6 ) of squamous cell carcinoma. There were inconsistent evaluation results using the ICMM tools of standard-based matrix and calculated risk rating. There were very high risks to be attacked by rhinocarcinoma of the workers who exposed to wood dust for the tool of calculated risk rating, while high risk for the tool of standard-based matrix. For the workers who exposed to noise, risk of noise-induced deafness was unacceptable and medium risk using two tools, respectively. Conclusion: Both EPA model and ICMM model can appropriately predict and assessthe occupational health risk in wooden furniture manufactory, ICMM due to the relatively simple operation, easy evaluation parameters, assessment of occupational - disease - inductive factors comprehensively, and more suitable for wooden furniture production enterprise.

Cancer-related fatigue: Mechanisms, risk factors, and treatments

Science.gov (United States)

Bower, Julienne E.

2015-01-01

Fatigue is one of the most common and distressing side effects of cancer and its treatment, and may persist for years after treatment completion in otherwise healthy survivors. Cancer-related fatigue causes disruption in all aspects of quality of life and may be a risk factor for reduced survival. The prevalence and course of fatigue in cancer patients has been well characterized, and there is growing understanding of underlying biological mechanisms. Inflammation has emerged as a key biological pathway for cancer-related fatigue, with studies documenting links between markers of inflammation and fatigue before, during, and particularly after treatment. There is considerable variability in the experience of cancer-related fatigue that is not explained by disease- or treatment-related characteristics, suggesting that host factors may play an important role in the development and persistence of this symptom. Indeed, longitudinal studies have begun to identify genetic, biological, psychosocial, and behavioral risk factors for cancer-related fatigue. Given the multi-factorial nature of cancer-related fatigue, a variety of intervention approaches have been examined in randomized controlled trials, including physical activity, psychosocial, mind-body, and pharmacological treatments. Although there is currently no gold standard for treating fatigue, several of these approaches have shown beneficial effects and can be recommended to patients. This report provides a state of the science review of mechanisms, risk factors, and interventions for cancer-related fatigue, with a focus on recent longitudinal studies and randomized trials that have targeted fatigued patients. PMID:25113839

Evaluating nonindigenous species management in a Bayesian networks derived relative risk framework for Padilla Bay, WA, USA.

Science.gov (United States)

Herring, Carlie E; Stinson, Jonah; Landis, Wayne G

2015-10-01

Many coastal regions are encountering issues with the spread of nonindigenous species (NIS). In this study, we conducted a regional risk assessment using a Bayesian network relative risk model (BN-RRM) to analyze multiple vectors of NIS introductions to Padilla Bay, Washington, a National Estuarine Research Reserve. We had 3 objectives in this study. The 1st objective was to determine whether the BN-RRM could be used to calculate risk from NIS introductions for Padilla Bay. Our 2nd objective was to determine which regions and endpoints were at greatest risk from NIS introductions. Our 3rd objective was to incorporate a management option into the model and predict endpoint risk if it were to be implemented. Eradication can occur at different stages of NIS invasions, such as the elimination of these species before being introduced to the habitat or removal of the species after settlement. We incorporated the ballast water treatment management scenario into the model, observed the risk to the endpoints, and compared this risk with the initial risk estimates. The model results indicated that the southern portion of the bay was at greatest risk because of NIS. Changes in community composition, Dungeness crab, and eelgrass were the endpoints most at risk from NIS introductions. The currents node, which controls the exposure of NIS to the bay from the surrounding marine environment, was the parameter that had the greatest influence on risk. The ballast water management scenario displayed an approximate 1% reduction in risk in this Padilla Bay case study. The models we developed provide an adaptable template for decision makers interested in managing NIS in other coastal regions and large bodies of water. © 2015 SETAC.

Adding an alcohol-related risk score to an existing categorical risk classification for older adults: sensitivity to group differences.

Science.gov (United States)

Wilson, Sandra R; Fink, Arlene; Verghese, Shinu; Beck, John C; Nguyen, Khue; Lavori, Philip

2007-03-01

To evaluate a new alcohol-related risk score for research use. Using data from a previously reported trial of a screening and education system for older adults (Computerized Alcohol-Related Problems Survey), secondary analyses were conducted comparing the ability of two different measures of risk to detect post-intervention group differences: the original categorical outcome measure and a new, finely grained quantitative risk score based on the same research-based risk factors. Three primary care group practices in southern California. Six hundred sixty-five patients aged 65 and older. A previously calculated, three-level categorical classification of alcohol-related risk and a newly developed quantitative risk score. Mean post-intervention risk scores differed between the three experimental conditions: usual care, patient report, and combined report (Ptrinary risk classification. The additional clinical value of the risk score relative to the categorical measure needs to be determined.