Risk Analysis: An International Journal

Subscribe to Risk Analysis: An International Journal feed Risk Analysis: An International Journal
Table of Contents for Risk Analysis. List of articles from both the latest and EarlyView issues.
Updated: 27 min 35 sec ago

Issue Information ‐ TOC

5 April 2019 - 7:47pm
Risk Analysis, Volume 39, Issue 4, April 2019.

Residents’ Reactions to Earthquake Early Warnings in Japan

29 March 2019 - 5:21pm
Abstract

This article empirically examines the effectiveness of earthquake early warning (EEW) in Japan based on experiences of residents who received warnings before earthquake shaking occurred. In Study 1, a survey (N = 299) was conducted to investigate residents’ experiences of, and reactions to, an EEW issued in Gunma and neighboring regions on June 17, 2018. The main results were as follows. (1) People's primary reactions to the EEW were mental, not physical, and thus motionless. Most residents stayed still, not for safety reasons, but because they were focusing on mentally bracing themselves. (2) Residents perceived the EEW to be effective because it enabled them to mentally prepare, rather than take physical protective actions, before strong shaking arrived. (3) In future, residents anticipate that on receipt of an EEW they would undertake mental preparation as opposed to physical protective actions. In Study 2, a survey (N = 450) was conducted on another EEW issued for an earthquake offshore of Chiba Prefecture on July 7, 2018. Results were in line with those of Study 1, suggesting that the findings described above are robust. Finally, given people's lack of impetus to undertake protective action on receipt of an EEW, this article discusses ways to enhance such actions.

A Multicompartment SIS Stochastic Model with Zonal Ventilation for the Spread of Nosocomial Infections: Detection, Outbreak Management, and Infection Control

29 March 2019 - 5:19pm
Abstract

In this work, we study the environmental and operational factors that influence airborne transmission of nosocomial infections. We link a deterministic zonal ventilation model for the airborne distribution of infectious material in a hospital ward, with a Markovian multicompartment SIS model for the infection of individuals within this ward, in order to conduct a parametric study on ventilation rates and their effect on the epidemic dynamics. Our stochastic model includes arrival and discharge of patients, as well as the detection of the outbreak by screening events or due to symptoms being shown by infective patients. For each ventilation setting, we measure the infectious potential of a nosocomial outbreak in the hospital ward by means of a summary statistic: the number of infections occurred within the hospital ward until end or declaration of the outbreak. We analytically compute the distribution of this summary statistic, and carry out local and global sensitivity analysis in order to identify the particular characteristics of each ventilation regime with the largest impact on the epidemic spread. Our results show that ward ventilation can have a significant impact on the infection spread, especially under slow detection scenarios or in overoccupied wards, and that decreasing the infection risk for the whole hospital ward might increase the risk in specific areas of the health‐care facility. Moreover, the location of the initial infective individual and the protocol in place for outbreak declaration both form an interplay with ventilation of the ward.

Peak Exposures in Epidemiologic Studies and Cancer Risks: Considerations for Regulatory Risk Assessment

29 March 2019 - 5:19pm
Abstract

We review approaches for characterizing “peak” exposures in epidemiologic studies and methods for incorporating peak exposure metrics in dose–response assessments that contribute to risk assessment. The focus was on potential etiologic relations between environmental chemical exposures and cancer risks. We searched the epidemiologic literature on environmental chemicals classified as carcinogens in which cancer risks were described in relation to “peak” exposures. These articles were evaluated to identify some of the challenges associated with defining and describing cancer risks in relation to peak exposures. We found that definitions of peak exposure varied considerably across studies. Of nine chemical agents included in our review of peak exposure, six had epidemiologic data used by the U.S. Environmental Protection Agency (US EPA) in dose–response assessments to derive inhalation unit risk values. These were benzene, formaldehyde, styrene, trichloroethylene, acrylonitrile, and ethylene oxide. All derived unit risks relied on cumulative exposure for dose–response estimation and none, to our knowledge, considered peak exposure metrics. This is not surprising, given the historical linear no‐threshold default model (generally based on cumulative exposure) used in regulatory risk assessments. With newly proposed US EPA rule language, fuller consideration of alternative exposure and dose–response metrics will be supported. “Peak” exposure has not been consistently defined and rarely has been evaluated in epidemiologic studies of cancer risks. We recommend developing uniform definitions of “peak” exposure to facilitate fuller evaluation of dose response for environmental chemicals and cancer risks, especially where mechanistic understanding indicates that the dose response is unlikely linear and that short‐term high‐intensity exposures increase risk.

Managing Safety‐Related Disruptions: Evidence from the U.S. Nuclear Power Industry

29 March 2019 - 5:19pm
Abstract

Low‐probability, high‐impact events are difficult to manage. Firms may underinvest in risk assessments for low‐probability, high‐impact events because it is not easy to link the direct and indirect benefits of doing so. Scholarly research on the effectiveness of programs aimed at reducing such events faces the same challenge. In this article, we draw on comprehensive industry‐wide data from the U.S. nuclear power industry to explore the impact of conducting probabilistic risk assessment (PRA) on preventing safety‐related disruptions. We examine this using data from over 25,000 monthly event reports across 101 U.S. nuclear reactors from 1985 to 1998. Using Poisson fixed effects models with time trends, we find that the number of safety‐related disruptions reduced between 8% and 27% per month in periods after operators submitted their PRA in response to the Nuclear Regulatory Commission's Generic Letter 88‐20, which required all operators to conduct a PRA. One possible mechanism for this is that the adoption of PRA may have increased learning rates, lowering the rate of recurring events by 42%. We find that operators that completed their PRA before Generic Letter 88‐20 continued to experience safety improvements during 1990–1995. This suggests that revisiting PRA or conducting it again can be beneficial. Our results suggest that even in a highly safety‐conscious industry as nuclear utilities, a more formal approach to quantifying risk has its benefits.

Risk and the Five Hard Problems of Cybersecurity

29 March 2019 - 5:19pm
Abstract

This perspectives article addresses risk in cyber defense and identifies opportunities to incorporate risk analysis principles into the cybersecurity field. The Science of Security (SoS) initiative at the National Security Agency seeks to further and promote interdisciplinary research in cybersecurity. SoS organizes its research into the Five Hard Problems (5HP): (1) scalability and composability; (2) policy‐governed secure collaboration; (3) security‐metrics–driven evaluation, design, development, and deployment; (4) resilient architectures; and (5) understanding and accounting for human behavior. However, a vast majority of the research sponsored by SoS does not consider risk and when it does so, only implicitly. Therefore, we identify opportunities for risk analysis in each hard problem and propose approaches to address these objectives. Such collaborations between risk and cybersecurity researchers will enable growth and insight in both fields, as risk analysts may apply existing methodology in a new realm, while the cybersecurity community benefits from accepted practices for describing, quantifying, working with, and mitigating risk.

Trends in Multidisciplinary Hazard and Disaster Research: A 1982–2017 Case Study

28 March 2019 - 3:26pm
Abstract

From 1982 to 2017, 539 unique awards studying extreme events and natural disasters have been funded by the Infrastructure Management and Extreme Events (IMEE), Decision, Risk and Management Science (DRMS), Humans, Disasters, and the Built Environment (HDBE), and Hazard Science, Engineering, and Education for Sustainability (Hazard SEES) programs under the National Science Foundation, totaling approximately $450 million. The relationships between discipline, topic, and funding are explored through review of the data on each award's active dates, amount of funding received, specific hazards and disasters studied, and principal investigator (PI) and co‐PI affiliations. A positive correlation between award funding and increasingly larger multidisciplinary teams of PIs on projects is observed. However, these teams of four or more PIs only account for about 18% of the total number of awards. In terms of topic, projects applicable to general hazard/disaster research encompass the largest portion of awards, but not the greatest funding per award on average. Additionally, both the number of awards per year and the total funds allotted per year show an increasing trend. Finally, some of the trends in project team discipline with relation to hazards show a shift to equal numbers of engineers and social scientists on multidisciplinary teams while others remain fairly homogeneous in their team dynamics. This article provides unique perspectives on how to better allocate funds through extensive topic and funding analysis. This work is a brief analysis of trends in the hazard and disaster research community, focusing on multidisciplinary project teams and their correlation to funding amounts and research areas.

A Definition and Categorization System for Advanced Materials: The Foundation for Risk‐Informed Environmental Health and Safety Testing

25 March 2019 - 5:15pm
Abstract

Novel materials with unique or enhanced properties relative to conventional materials are being developed at an increasing rate. These materials are often referred to as advanced materials (AdMs) and they enable technological innovations that can benefit society. Despite their benefits, however, the unique characteristics of many AdMs, including many nanomaterials, are poorly understood and may pose environmental safety and occupational health (ESOH) risks that are not readily determined by traditional risk assessment methods. To assess these risks while keeping up with the pace of development, technology developers and risk assessors frequently employ risk‐screening methods that depend on a clear definition for the materials that are to be assessed (e.g., engineered nanomaterial) as well as a method for binning materials into categories for ESOH risk prioritization. The term advanced material lacks a consensus definition and associated categorization or grouping system for risk screening. In this study, we aim to establish a practitioner‐driven definition for AdMs and a practitioner‐validated framework for categorizing AdMs into conceptual groupings based on material characteristics. Results from multiple workshops and interviews with practitioners provide consistent differentiation between AdMs and conventional materials, offer functional nomenclature for application science, and provide utility for future ESOH risk assessment prioritization. The definition and categorization framework established here serve as a first step in determining if and when there is a need for specific ESOH and regulatory screening for an AdM as well as the type and extent of risk‐related information that should be collected or generated for AdMs and AdM‐enabled technologies.

Experiments in Lay Cues to the Relative Validity of Positions Taken by Disputing Groups of Scientists

25 March 2019 - 5:14pm
Abstract

Risk analysis and hazard management can prompt varied intra‐scientific disputes, some which have or will become public, and thus potentially available for lay judgments of the relative validity of the positions taken. As attentive laypeople may include elites as well as the general public, understanding whether and how cues to credibility of disputing groups of scientists might shape those lay judgments can be important. Relevant literatures from philosophy, social studies of science, risk analysis, and elsewhere have identified potential cues, but not tested their absolute or relative effects. Two experiments with U.S. online panel members tested multiple cues (e.g., credentials, experience, majority opinions, research quality) across topics varying in familiarity subject to actual intra‐science disputes (dark matter, marijuana, sea‐level rise). If cues supported a position, laypeople were more likely to choose it as relatively more valid, with information quality, majority “vote,” experience, and degree source as the strongest, and interest, demographic, and values similarity as the weakest, cues. These results were similar in overall rankings to those from implicit rankings of cue reliability ratings from an earlier U.S. online survey. Proposed moderators were generally nonsignificant, but topic familiarity and subjective topic knowledge tended to reduce cue effects. Further research to confirm and extend these findings can inform both theory about citizen engagement with scientific and risk disputes, and practice in communication about science and risk.

Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System

20 March 2019 - 4:12pm
Abstract

Multiple hazard resilience is of significant practical value because most regions of the world are subject to multiple natural and technological hazards. An analysis and assessment approach for multiple hazard spatiotemporal resilience of interdependent infrastructure systems is developed using network theory and a numerical analysis. First, we define multiple hazard resilience and present a quantitative probabilistic metric based on the expansion of a single hazard deterministic resilience model. Second, we define a multiple hazard relationship analysis model with a focus on the impact of hazards on an infrastructure. Subsequently, a relationship matrix is constructed with temporal and spatial dimensions. Further, a general method for the evaluation of direct impacts on an individual infrastructure under multiple hazards is proposed. Third, we present an analysis of indirect multiple hazard impacts on interdependent infrastructures and a joint restoration model of an infrastructure system. Finally, a simplified two‐layer interdependent infrastructure network is used as a case study for illustrating the proposed methodology. The results show that temporal and spatial relationships of multiple hazards significantly influence system resilience. Moreover, the interdependence among infrastructures further magnifies the impact on resilience value. The main contribution of the article is a new multiple hazard resilience evaluation approach that is capable of integrating the impacts of multiple hazard interactions, interdependence of network components (layers), and restoration strategy.

A Modular Bayesian Salmonella Source Attribution Model for Sparse Data

20 March 2019 - 4:09pm
Abstract

Several statistical models for salmonella source attribution have been presented in the literature. However, these models have often been found to be sensitive to the model parameterization, as well as the specifics of the data set used. The Bayesian salmonella source attribution model presented here was developed to be generally applicable with small and sparse annual data sets obtained over several years. The full Bayesian model was modularized into three parts (an exposure model, a subtype distribution model, and an epidemiological model) in order to separately estimate unknown parameters in each module. The proposed model takes advantage of the consumption and overall salmonella prevalence of the studied sources, as well as bacteria typing results from adjacent years. The latter were used for a smoothed estimation of the annual relative proportions of different salmonella subtypes in each of the sources. The source‐specific effects and the salmonella subtype‐specific effects were included in the epidemiological model to describe the differences between sources and between subtypes in their ability to infect humans. The estimation of these parameters was based on data from multiple years. Finally, the model combines the total evidence from different modules to proportion human salmonellosis cases according to their sources. The model was applied to allocate reported human salmonellosis cases from the years 2008 to 2015 to eight food sources.

Communicating with the Public About Marauding Terrorist Firearms Attacks: Results from a Survey Experiment on Factors Influencing Intention to “Run, Hide, Tell” in the United Kingdom and Denmark

20 March 2019 - 4:08pm
Abstract

Effective risk communication is an integral part of responding to terrorism, but until recently, there has been very little pre‐event communication in a European context to provide advice to the public on how to protect themselves during an attack. Following terrorist attacks involving mass shootings in Paris, France, in November 2015, the U.K. National Police Chiefs’ Council released a Stay Safe film and leaflet that advises the public to “run,” “hide,” and “tell” in the event of a firearms or weapons attack. However, other countries, including Denmark, do not provide preparedness information of this kind, in large part because of concern about scaring the public. In this survey experiment, 3,003 U.K. and Danish participants were randomly assigned to one of three conditions: no information, a leaflet intervention, and a film intervention to examine the impact of “Run, Hide, Tell” advice on perceptions about terrorism, the security services, and intended responses to a hypothetical terrorist firearms attack. Results demonstrate important benefits of pre‐event communication in relation to enhancing trust, encouraging protective health behaviors, and discouraging potentially dangerous actions. However, these findings also suggest that future communications should address perceived response costs and target specific problem behaviors. Cross‐national similarities in response suggest this advice is suitable for adaptation in other countries.

Toward Convergence Disaster Research: Building Integrative Theories Using Simulation

18 March 2019 - 7:00pm
Abstract

Scholars across disciplines use simulation methods as tools to build theories; however, the full potential of simulation methods has not been fully used for building theories in convergence disaster research. Simulation methods could provide four unique opportunities for building theories for convergence disaster research. First, simulation methods could help researchers model the underlying mechanisms of disaster phenomena by enabling integration of qualitative and quantitative data. Second, they could help researchers specify and characterize the mechanisms affecting specific disaster phenomena by facilitating integration of empirical information with existing theoretical elements from different disciplines. Third, simulation methods could enable multilevel understanding of relationships between factors influencing disaster phenomena and emergent behaviors across different levels of analysis (e.g., individual, household, neighborhood, and community levels). Fourth, simulation methods could help researchers integrate theoretical elements on disasters across different disciplines (e.g., engineering, social science, sociology, and epidemiology) for a more convergent understanding of complex relationships affecting resilience at different levels.

Risk Communication as Government Agency Organizational Practice

18 March 2019 - 10:05am
Abstract

The dynamics of organizational risk communication is an understudied topic in risk research. This article investigates how public officials at six government agencies in Sweden understand and relate to risk communication and its uses in the context of agency organizational work on policy and regulation. Qualitative interviews were used to explore the practitioners’ views on some key topics in the academic literature on risk communication. A main finding is that there is little consensus on what the goals of risk communication are; if, and how, uncertainty should be communicated; and what role is to be played by transparency in risk communication. However, the practitioners agree that dissemination (top down) to the public of robust scientific and expert knowledge is a crucial element. Dialogue and participation is used mainly with other agencies and elite stakeholders with whom agencies collaborate to implement policy goals. Dialogue with the public on issues of risk is very limited. Some implications of the findings for the practice of risk communication by government agencies are suggested.

Cigarette Smoking and Multiple Health Risk Behaviors: A Latent Class Regression Model to Identify a Profile of Young Adolescents

12 March 2019 - 7:58pm
Abstract

Cigarette smoking is often established during adolescence when other health‐related risk behaviors tend to occur. The aim of the study was to further investigate the hypothesis that risky health behaviors tend to cluster together and to identify distinctive profiles of young adolescents based on their smoking habits. To explore the idea that smoking behavior can predict membership in a specific risk profile of adolescents, with heavy smokers being more likely to exhibit other risk behaviors, we reanalyzed the data from the 2014 Health Behaviour in School‐Aged Children Italian survey of about 60,000 first‐ and third‐grade junior high school (JHS) and second‐grade high school (HS) students. A Bayesian approach was adopted for selecting the manifest variables associated with smoking; a latent class regression model was employed to identify smoking behaviors among adolescents. Finally, a health‐related risk pattern associated with different types of smoking behaviors was found. Heavy smokers engaged in higher alcohol use and abuse and experienced school failure more often than their peers. Frequent smokers reported below‐average academic achievement and self‐rated their health as fair/poor more frequently than nonsmokers. Lifetime cannabis use and early sexual intercourse were more frequent among heavy smokers. Our findings provide elements for constructing a profile of frequent adolescent smokers and for identifying behavioral risk patterns during the transition from JHS to HS. This may provide an additional opportunity to devise interventions that could be more effective to improve smoking cessation among occasional smokers and to adequately address other risk behaviors among frequent smokers.

Cigarette Smoking and Multiple Health Risk Behaviors: A Latent Class Regression Model to Identify a Profile of Young Adolescents

12 March 2019 - 7:58pm
Abstract

Cigarette smoking is often established during adolescence when other health‐related risk behaviors tend to occur. The aim of the study was to further investigate the hypothesis that risky health behaviors tend to cluster together and to identify distinctive profiles of young adolescents based on their smoking habits. To explore the idea that smoking behavior can predict membership in a specific risk profile of adolescents, with heavy smokers being more likely to exhibit other risk behaviors, we reanalyzed the data from the 2014 Health Behaviour in School‐Aged Children Italian survey of about 60,000 first‐ and third‐grade junior high school (JHS) and second‐grade high school (HS) students. A Bayesian approach was adopted for selecting the manifest variables associated with smoking; a latent class regression model was employed to identify smoking behaviors among adolescents. Finally, a health‐related risk pattern associated with different types of smoking behaviors was found. Heavy smokers engaged in higher alcohol use and abuse and experienced school failure more often than their peers. Frequent smokers reported below‐average academic achievement and self‐rated their health as fair/poor more frequently than nonsmokers. Lifetime cannabis use and early sexual intercourse were more frequent among heavy smokers. Our findings provide elements for constructing a profile of frequent adolescent smokers and for identifying behavioral risk patterns during the transition from JHS to HS. This may provide an additional opportunity to devise interventions that could be more effective to improve smoking cessation among occasional smokers and to adequately address other risk behaviors among frequent smokers.

The Use of Telematics Devices to Improve Automobile Insurance Rates

7 March 2019 - 1:13pm
Abstract

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay‐as‐you‐drive sample of insureds. We include distance traveled per year as part of an offset in a zero‐inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.

The Impact of Portfolio Location Uncertainty on Probabilistic Seismic Risk Analysis

7 March 2019 - 1:13pm
Abstract

Probabilistic seismic risk analysis is a well‐established method in the insurance industry for modeling portfolio losses from earthquake events. In this context, precise exposure locations are often unknown. However, so far, location uncertainty has not been in the focus of a large amount of research. In this article, we propose a novel framework for treatment of location uncertainty. As a case study, a large number of synthetic portfolios resembling typical real‐world cases were created. We investigate the effect of portfolio characteristics such as value distribution, portfolio size, or proportion of risk items with unknown coordinates on the variability of loss frequency estimations. The results indicate that due to loss aggregation effects and spatial hazard variability, location uncertainty in isolation and in conjunction with ground motion uncertainty can induce significant variability to probabilistic loss results, especially for portfolios with a small number of risks. After quantifying its effect, we conclude that location uncertainty should not be neglected when assessing probabilistic seismic risk, but should be treated stochastically and the resulting variability should be visualized and interpreted carefully.

An Insurance Model for Risk Management of Process Facilities

7 March 2019 - 1:13pm
Abstract

Most existing risk management models for process industries do not consider the effect of insurance coverage, which results in an overestimation of overall risk. A model is presented in this article to study the effect of insurance coverage of health, safety, environmental, and business risks. The effect of insurance recovery is modeled through the application of adjustment factors by considering the stochastic factors affecting insurance recovery. The insurance contract's conditions, deductibles, and policy limits are considered in developing the insurance recovery adjustment factors. Copula functions and Monte Carlo simulations are used to develop the distribution of the aggregate loss by considering the dependence among loss classes. A case study is used to demonstrate both the practical application of the proposed insurance model to improve management decisions, and the mitigating effect of insurance to minimize the residual risk.

Pages