scholarly journals Probabilistic models for risk assessment of disasters

2011 ◽  
Author(s):  
A. Lepikhin ◽  
I. Lepikhina
Keyword(s):  
Risk Assessment ◽  
Probabilistic Models

Methodology for risk assessment of agribusiness enterprises: content and algorithm of implementation for modeling purposes

2020 ◽  
pp. 236-245
Author(s):  
В.М. Безденежных ◽  
Л.Х. Боташева ◽  
Д.Ф. Ализада
Keyword(s):  
Risk Assessment ◽  
Pareto Optimality ◽  
Probabilistic Models ◽  
Agricultural Sector ◽  
Optimality Criterion ◽  
Agricultural Products ◽  
Static Picture ◽  
Methodological Approaches ◽  
Dynamic Series

В статье исследуются методики оценки рисков аграрного сектора экономики на основе вероятностных моделей, учитывающих особенности самих рисков и размеры потерь сельскохозяйственной продукции. Показано, что два различных по своей сути методических подхода (принципа пропорции Парето и критерий оптимальности Парето) моделирования могут хорошо дополнять друг друга, создавая статическую картину события и динамический ряд ее изменений. The article explores methods of assessing risks of the agricultural sector of the economy on the basis of probabilistic models, taking into account the peculiarities of risks themselves and the size of losses of agricultural products. It is two different methodological approaches (the Pareto proportion principle and the Pareto optimality criterion) of modeling as complement each other, creating a static picture of the event and a dynamic series of its changes.

scholarly journals Challenges in risk assessment of multiple mycotoxins in food

2016 ◽  
Vol 9 (5) ◽  
pp. 791-811 ◽  
Author(s):  
R. Assunção ◽  
M.J. Silva ◽  
P. Alvito
Keyword(s):  
Risk Assessment ◽  
Exposure Assessment ◽  
Hazard Assessment ◽  
Human Exposure ◽  
Probabilistic Models ◽  
Deep Understanding ◽  
Data Availability ◽  
Interactive Effects ◽  
Knowledge Generation ◽  
Experimental Conditions

Most fungi are able to produce several mycotoxins simultaneously and, consequently, to contaminate a wide variety of foodstuffs. Therefore, the risk of human co-exposure to multiple mycotoxins is real, raising a growing concern about their potential impact on human health. Besides, government and industry regulations are usually based on individual toxicities, and do not take into account the complex dynamics associated with interactions between co-occurring groups of mycotoxins. The present work assembles, for the first time, the challenges posed by the likelihood of human co-exposure to these toxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment. Regarding hazard assessment, a physiologically-based framework is proposed in order to infer the health effects from exposure to multiple mycotoxins in food, including knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of single and combined toxins. The prioritisation of the most relevant mixtures to be tested under experimental conditions that attempt to mimic human exposure and the use of adequate mathematical approaches to evaluate interactions, particularly concerning the combined genotoxicity, were identified as the main challenges for hazard assessment. Regarding exposure assessment, the need of harmonised food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data, use of probabilistic models and multibiomarker approaches are highlighted, in order to develop a more precise and realistic exposure assessment. To conclude, further studies on hazard and exposure assessment of multiple mycotoxins, using harmonised methodologies, are crucial towards an improvement of data quality and a more reliable and robust risk characterisation, which is central for risk management and, consequently, to prevent mycotoxins-associated adverse effects. A deep understanding of the nature of interactions between multiple mycotoxins will contribute to draw real conclusions on the health impact of human exposure to mycotoxin mixtures.

Variable resolution probabilistic modeling of residential exposure and vulnerability for risk applications

2020 ◽  
Vol 36 (1_suppl) ◽  
pp. 321-344 ◽  
Author(s):  
Massimiliano Pittore ◽  
Michael Haas ◽  
Vitor Silva
Keyword(s):  
Risk Assessment ◽  
Survey Data ◽  
Natural Hazards ◽  
Large Scale ◽  
Probabilistic Models ◽  
Probabilistic Framework ◽  
Variable Resolution ◽  
Exposure Modeling ◽  
Scale Models

In risk assessment, the exposure component describes the elements exposed to the natural hazards and susceptible to damage or loss, while the vulnerability component defines the likelihood to incur damage or loss conditional on a given level of hazard intensity. In this article, we propose a novel adaptive approach to exposure modeling which exploits Dirichlet-Multinomial Bayesian updating to implement the incremental assimilation of sparse in situ survey data into probabilistic models described by compositions (proportions). This methodology is complemented by the introduction of a custom spatial aggregation support based on variable-resolution Central Voronoidal Tessellations. The proposed methodology allows for a more consistent integration of empirical observations, typically from engineering surveys, into large-scale models that can also efficiently exploit expert-elicited knowledge. The resulting models are described in a probabilistic framework, and as such allow for a more thorough analysis of the underlying uncertainty. The proposed approach is applied and discussed in five countries in Central Asia.

From Epidemiologic Exposure and Risk Assessment to Probabilistic Models: Experience with the Investigation of Health Effects of Soil Contamination in Germany

1997 ◽  
Vol 16 (4-5) ◽  
pp. 391-418 ◽  
Author(s):  
H.-Erich Wichmann ◽  
Mary Jo Trepka ◽  
Joachim Heinrich ◽  
Wolfgang Ihme ◽  
Odile Mekel ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Health Risks ◽  
Contaminated Soil ◽  
Hot Spots ◽  
Probabilistic Models ◽  
Probability Distributions ◽  
Epidemiological Studies ◽  
Worst Case ◽  
Quantitative Estimates ◽  
Reasonable Answers

Exposure and risk assessment can be based on direct epidemiological investigations that study exposed individuals or on models. Examples from situations in Germany for both approaches are presented and discussed here. Epidemiological studies for the health risk assessment of contaminated soil typically have one or more of the following problems: the number of exposed persons is too small: critical confounders cannot be measured and controlled for appropriately; or the expected effects are not large enough to be detected. Therefore, at least for most situations in Germany, epidemiological investigations designed to measure health risks infrequently provide clear answers. In contrast, direct epidemiological investigations are more likely to be able to quantify exposure. If the soil concentrations are high, one is able to identify the location of relevant “hot spots” using biological and environmental monitoring. Further, epidemiology can be used to get information about the distribution of exposure in specific populations, such as young children or amateur gardeners. Exposure assessment by modeling provides answers in situations in which no reasonable answers can be expected using epidemiological means. The model gives quantitative estimates for average and reasonable worst-case situations. The latter can be determined by modeling probability distributions.

Probabilistic Seismic Response Models for Risk Assessment and Design of Steel Moment Frames with Linear Viscous Dampers

2019 ◽  
Vol 35 (1) ◽  
pp. 267-288 ◽  
Author(s):  
Omid Dadpour ◽  
Mehdi Banazadeh
Keyword(s):  
Risk Assessment ◽  
Seismic Response ◽  
Seismic Risk ◽  
Probabilistic Models ◽  
Design Procedure ◽  
Structural Response ◽  
Principal Component ◽  
Moment Frames ◽  
Intensity Measures ◽  
Design Variables

The use of supplemental viscous damping significantly improves the seismic performance of buildings; however, a design procedure that considers seismic risk is necessary. The aim of this article is to simplify the seismic risk assessment of mid-rise steel frames with linear viscous fluid dampers by employing probabilistic models and a reliability analysis. The development of a probabilistic seismic response model (PSRM) to predict the structural response without performing extensive computation is a principal component of this methodology. The design and modeling of generic frames, record selection, cloud analysis, assessment of candidate intensity measures, and use of vector-valued intensity measures are the primary aspects of this study, the goal of which is to put forward a PSRM for the target frames. Comparison of the PSRM outcome with the results of case studies demonstrates the acceptable accuracy of the models for the design earthquake; these models lead to a reduction in the computation and complexity involved in selecting design variables to achieve a target risk.

scholarly journals Sociotechnical risk assessment for water distribution system contamination threats

2013 ◽  
Vol 16 (3) ◽  
pp. 531-549 ◽  
Author(s):  
Amin Rasekh ◽  
M. Ehsan Shafiee ◽  
Emily Zechman ◽  
Kelly Brumbelow
Keyword(s):  
Public Health ◽  
Risk Assessment ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Probabilistic Models ◽  
Health Consequences ◽  
Multi Objective ◽  
Contamination Event ◽  
Contamination Events

Water distribution systems (WDS) are vulnerable to contaminants, and systematic risk assessment can provide valuable information for assisting threat management. Contamination events are sociotechnical systems, in which the interactions among consumers and water infrastructure may generate unpredicted public health consequences. This research develops a sociotechnical risk assessment framework that simulates the dynamics of a contamination event by coupling an agent-based modeling (ABM) framework with Monte Carlo simulation (MCS), genetic algorithm (GA) optimization, and a multi-objective GA. The ABM framework couples WDS simulation with agents to represent consumers in a virtual city. MCS is applied to estimate the uncertainty in human exposure, based on probabilistic models of event attributes. A GA approach is used to identify critical contamination events by maximizing risk, and a multi-objective approach explores the trade-off between consequence and occurrence probabilities. Results that are obtained using the sociotechnical approach are compared with results obtained using a conventional engineering model. The sociotechnical approach removes assumptions that have been used in engineering analysis about the static, homogeneous, and stationary behaviors of consumers, and results demonstrate new insight about the impacts of these actions and interactions on the public health consequences of contamination events.

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