Avaliação probabilística de riscos à saúde humana em área contaminada por compostos organoclorados

Introdução: Áreas contaminadas por agentes químicos perigosos em regiões urbanas representam riscos importantes à saúde humana e ao ambiente. Vila Carioca, localizada na cidade de São Paulo, é uma área contaminada por pesticidas organoclorados considerada crítica, pela magnitude da contaminação, pela presença de pessoas residentes e pela complexidade de fontes da contaminação. Vários estudos de riscos já foram realizados por uma das empresas contaminadoras, no entanto, ainda há muita incerteza e controvérsias sobre os riscos à saúde da população. Objetivo: Avaliar o incremento de risco de câncer no tempo de vida para população exposta por meio de uma avaliação probabilística. Método: Foram utilizados dados secundários das contaminações obtidos nos estudos de riscos efetuados pela empresa produtora de pesticidas organoclorados e também em documentos oficiais dos órgãos de saúde e meio ambiente do Estado de São Paulo, resultantes do monitoramento da água e do solo na área residencial no período de 1997 a 2012, para 335 substâncias. Foram selecionadas substâncias carcinogênicas presentes na água subterrânea e solo com melhor conjunto de dados. Para a avaliação probabilística foi empregado o método de simulação de Monte Carlo, por meio do software comercial ModelRisk. Foram utilizados os métodos recomendados pela United States Environmental Protection Agency para a avaliação de risco de exposição dérmica e de incremento de riscos de câncer para substâncias mutagênicas. Foram consideradas a ingestão de água e solo, e contato dérmico com água. Resultados: O incremento de risco de câncer no tempo de vida (IRLT) foi de 4,7x10-3 e 4,1x10-2 para o percentil 50% e 95%, respectivamente. As rotas de exposição mais importantes foram ingestão e contato dérmico com a água subterrânea, seguido da ingestão de solo. O grupo etário que apresentou maior risco foi o das crianças de 0 a 2 anos de idade. Conclusão: Os riscos estimados são superiores aos valores considerados toleráveis. A avaliação realizada foi conservativa, mas ressalta-se que a restrição do uso da água subterrânea deve ser mantida e que a população deve ser devidamente informada dos riscos envolvidos na área, em especial, relacionados ao solo contaminado

MULTI-UNIT ACCIDENT CONTRIBUTIONS TO U.S. NUCLEAR REGULATORY COMMISSION QUANTITATIVE HEALTH OBJECTIVES: A SAFETY GOAL POLICY ANALYSIS USING MODELS FROM STATE-OF-THE-ART REACTOR CONSEQUENCE ANALYSES

The U.S. Nuclear Regulatory Commission implemented a safety goal policy in response to the 1979 Three Mile Island accident. This policy addresses the question “How safe is safe enough?” by specifying quantitative health objectives (QHOs) for comparison with results from nuclear power plant (NPP) probabilistic risk analyses (PRAs) to determine whether proposed regulatory actions are justified based on potential safety benefit. Lessons learned from recent operating experience—including the 2011 Fukushima accident—indicate that accidents involving multiple units at a shared site can occur with non-negligible frequency. Yet risk contributions from such scenarios are excluded by policy from safety goal evaluations—even for the nearly 60% of U.S. NPP sites that include multiple units. This research develops and applies methods for estimating risk metrics for comparison with safety goal QHOs using models from state-of-the-art consequence analyses to evaluate the effect of including multi-unit accident risk contributions in safety goal evaluations.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

Probabilistic-based hurricane risk assessment and mitigation considering the potential impacts of climate change

Studies are suggesting that hurricane hazard patterns (e.g. intensity and frequency) may change as a consequence of the changing global climate. As hurricane patterns change, it can be expected that hurricane damage risks and costs may change as a result. This indicates the necessity to develop hurricane risk assessment models that are capable of accounting for changing hurricane hazard patterns, and develop hurricane mitigation and climatic adaptation strategies. This thesis proposes a comprehensive hurricane risk assessment and mitigation strategies that account for a changing global climate and that has the ability of being adapted to various types of infrastructure including residential buildings and power distribution poles. The framework includes hurricane wind field models, hurricane surge height models and hurricane vulnerability models to estimate damage risks due to hurricane wind speed, hurricane frequency, and hurricane-induced storm surge and accounts for the timedependant properties of these parameters as a result of climate change. The research then implements median insured house values, discount rates, housing inventory, etc. to estimate hurricane damage costs to residential construction. The framework was also adapted to timber distribution poles to assess the impacts climate change may have on timber distribution pole failure. This research finds that climate change may have a significant impact on the hurricane damage risks and damage costs of residential construction and timber distribution poles. In an effort to reduce damage costs, this research develops mitigation/adaptation strategies for residential construction and timber distribution poles. The costeffectiveness of these adaptation/mitigation strategies are evaluated through the use of a Life-Cycle Cost (LCC) analysis. In addition, a scenario-based analysis of mitigation strategies for timber distribution poles is included. For both residential construction and timber distribution poles, adaptation/mitigation measures were found to reduce damage costs. Finally, the research develops the Coastal Community Social Vulnerability Index (CCSVI) to include the social vulnerability of a region to hurricane hazards within this hurricane risk assessment. This index quantifies the social vulnerability of a region, by combining various social characteristics of a region with time-dependant parameters of hurricanes (i.e. hurricane wind and hurricane-induced storm surge). Climate change was found to have an impact on the CCSVI (i.e. climate change may have an impact on the social vulnerability of hurricane-prone regions).

Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes’ theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment.

Probabilistic assessment of risk from the exposure to mercury in artisanal gold mining communities in Colombia

Colombia is one the largest per capita mercury polluters as a consequence of its artisanal gold mining operations, which are steadily increasing following the rising price of this metal. Compared to gravimetric separation methods and cyanidation, the concentration of gold using Hg amalgams presents several advantages: the process is less time-consuming and minimizes gold losses, and Hg is easily transported and inexpensive relative to the selling price of gold. Very often, mercury amalgamation is carried out on site by unprotected workers. During this operation large amounts of mercury are discharged to the environment and eventually reach the fresh water bodies in the vicinity where it is subjected to methylation. Additionally, as gold is released from the amalgam by heating on open charcoal furnaces in small workshops, mercury vapors are emitted and inhaled by the artisanal smelters and the general population

Developing a probabilistic graphical structure from a model of mental-health clinical risk expertise

This paper explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. The Galatean Risk Screening Tool [1] is a psychological model for mental health risk assessment based on fuzzy sets. This paper details how the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. These semantics are formalised by a detailed specification for an XML structure used to represent the expertise. The component parts were then mapped to equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements. © Springer-Verlag 2010.

Prevalence and social distribution of risk factors for chronic noncommunicable diseases in Brazil

OBJETIVOS: Evaluar los factores de riesgo de enfermedades crónicas no transmisibles (ECNT) e identificar las desigualdades sociales relacionadas con su distribución en la población adulta brasileña.MÉTODOS: Se estudiaron los factores de riesgo de ECNT (entre ellos el consumo de tabaco, el sobrepeso y la obesidad, el bajo consumo de frutas y vegetales [BCFV], la insuficiente actividad física en el tiempo de ocio [IAFTO], el estilo de vida sedentario y el consumo excesivo de alcohol) en una muestra probabilística de 54369 adultos de 26 capitales estatales de Brasil y el Distrito Federal en 2006. Se utilizó el Sistema de Vigilancia de los Factores Protectores y de Riesgo para Enfermedades Crónicas No Transmisibles por Entrevistas Telefónicas (VIGITEL), un sistema de encuestas telefónicas asistido por computadora, y se calcularon las prevalencias ajustadas por la edad para las tendencias en cuanto al nivel educacional mediante la regresión de Poisson con modelos lineales. RESULTADOS: Los hombres informaron mayor consumo de tabaco, sobrepeso, BCFV, estilo de vida sedentario y consumo excesivo de alcohol que las mujeres, pero menos IAFTO. En los hombres, la educación se asoció con un mayor sobrepeso y un estilo de vida sedentario, pero con un menor consumo de tabaco, BCFV e IAFTO. En las mujeres, la educación se asoció con un menor consumo de tabaco, sobrepeso, obesidad, BCFV e IAFTO, pero aumentó el estilo de vida sedentario CONCLUSIONES: En Brasil, la prevalencia de factores de riesgo para ECNT (excepto IAFTO) es mayor en los hombres que en las mujeres. En ambos sexos, el nivel de educación influye en la prevalencia de los factores de riesgo para ECNT

Risk premiums and benefit measures for generalized-expected-utility theories

Standard tools for the analysis of economic problems involving uncertainty, including risk premiums, certainty equivalents and the notions of absolute and relative risk aversion, are developed without making specific assumptions on functional form beyond the basic requirements of monotonicity, transitivity, continuity, and the presumption that individuals prefer certainty to risk. Individuals are not required to display probabilistic sophistication. The approach relies on the distance and benefit functions to characterize preferences relative to a given state-contingent vector of outcomes. The distance and benefit functions are used to derive absolute and relative risk premiums and to characterize preferences exhibiting constant absolute risk aversion (CARA) and constant relative risk aversion (CRRA). A generalization of the notion of Schur-concavity is presented. If preferences are generalized Schur concave, the absolute and relative risk premiums are generalized Schur convex, and the certainty equivalents are generalized Schur concave.

A practical approach to assess depression risk and to guide risk reduction strategies in later life

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.

Prevalence of trachoma in a population of the upper Rio Negro Basin and risk factors for active disease

Purpose: To determine the prevalence of trachoma in Sao Gabriel da Cachoeira (SGC), the only urban community of the upper Rio Negro Basin of the Amazon state in Brazil, near the Colombian border, and to investigate the risk factors associated with the active forms of the disease. Methods: A total of 1702 people (440 children up to 9 years and 1069 adults aged 15 years and above) were examined. The sample was selected from a probabilistic household sampling procedure based on census data and a previous study of trachoma prevalence in Sao Gabriel da Cachoeira. A two-stage probabilistic household cluster sample was drawn. Household units were randomly selected within each cluster. A variety of socioeconomic and hygiene variables were studied in order to determine the risk factors for active trachoma in a household. Results: The total prevalence of trachoma was 8.9%. Prevalence of active trachoma (TF and/or TI) in children aged 1-9 years was 11.1% and trachomatous trichiasis in adults aged 15 years and above was 0.19%. Trachomatous scarring reached a peak of 22.4% for subjects between 50 to 60 years of age. Corneal opacity occurred in subjects aged 50 years and older with a prevalence of 2.0%. No sex effect was found on the overall prevalence of trachoma in SGC. Risk factors associated with active trachoma were mainly related to poor socioeconomic indicators. Conclusions: Despite the ubiquitous presence of water, the analysis of the risk factors associated with the active forms of the disease supports the idea that a low personal standard of hygiene and not water availability per se, is the key factor associated with trachoma.

A probabilistic analysis of Clostridium perfringens growth during food service operations

The purpose of this study was threefold: first, the study was designed to illustrate the use of data and information collected in food safety surveys in a quantitative risk assessment. In this case, the focus was on the food service industry; however, similar data from other parts of the food chain could be similarly incorporated. The second objective was to quantitatively describe and better understand the role that the food service industry plays in the safety of food. The third objective was to illustrate the additional decision-making information that is available when uncertainty and variability are incorporated into the modelling of systems. (C) 2002 Elsevier Science B.V. All rights reserved.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.