Risk Analysis: An International Journal

Consumption of Fish and Shrimp from Southeast Louisiana Poses No Unacceptable Lifetime Cancer Risks Attributable to High-Priority Polycyclic Aromatic Hydrocarbons

13 March 2018 - 9:40pm
Abstract

Following oil spills such as the Deepwater Horizon accident (DWH), contamination of seafood resources and possible increased health risks attributable to consumption of seafood in spill areas are major concerns. In this study, locally harvested finfish and shrimp were collected from research participants in southeast Louisiana and analyzed for polycyclic aromatic hydrocarbons (PAHs). PAHs are some of the most important chemicals of concern regarding oil-spill-contaminated seafood resources during and following oil spills. Some PAHs are considered carcinogens for risk assessment purposes, and currently, seven of these can be combined in lifetime cancer risk assessments using EPA approaches. Most PAHs were not detected in these samples (minimum detection limits ranged from 1.2 to 2.1 PPB) and of those that were detected, they were generally below 10 PPB. The pattern of detected PAHs suggested that the source of these chemicals in these seafood samples was not a result of direct contact with crude oil. Lifetime cancer risks were assessed using conservative assumptions and models in a probabilistic framework for the seven carcinogenic PAHs. Lifetime health risks modeled using this framework did not exceed a 1/10,000 cancer risk threshold. Conservative, health-protective deterministic estimates of the levels of concern for PAH chemical concentration and seafood intake rates were above the concentrations and intake rates modeled under this probabilistic framework. Taken together, consumption of finfish and shrimp harvested from southeast Louisiana following the DWH does not pose unacceptable lifetime cancer risks from these seven carcinogenic PAHs even for the heaviest possible consumers.

Mitigating Sports Injury Risks Using Internet of Things and Analytics Approaches

12 March 2018 - 4:06pm
Abstract

Sport injuries restrict participation, impose a substantial economic burden, and can have persisting adverse effects on health-related quality of life. The effective use of Internet of Things (IoT), when combined with analytics approaches, can improve player safety through identification of injury risk factors that can be addressed by targeted risk reduction training activities. Use of IoT devices can facilitate highly efficient quantification of relevant functional capabilities prior to sport participation, which could substantially advance the prevailing sport injury management paradigm. This study introduces a framework for using sensor-derived IoT data to supplement other data for objective estimation of each individual college football player's level of injury risk, which is an approach to injury prevention that has not been previously reported. A cohort of 45 NCAA Division I-FCS college players provided data in the form of self-ratings of persisting effects of previous injuries and single-leg postural stability test. Instantaneous change in body mass acceleration (jerk) during the test was quantified by a smartphone accelerometer, with data wirelessly transmitted to a secure cloud server. Injuries sustained from the beginning of practice sessions until the end of the 13-game season were documented, along with the number of games played by each athlete over the course of a 13-game season. Results demonstrate a strong prediction model. Our approach may have strong relevance to the estimation of injury risk for other physically demanding activities. Clearly, there is great potential for improvement of injury prevention initiatives through identification of individual athletes who possess elevated injury risk and targeted interventions.

A Framework to Understand Extreme Space Weather Event Probability

12 March 2018 - 4:05pm
Abstract

An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments.

Issue Information - TOC

8 March 2018 - 8:22pm

From the Editors

8 March 2018 - 8:22pm

Quantitative Uncertainty Analysis for a Weed Risk Assessment System

6 March 2018 - 9:35pm
Abstract

Weed risk assessments (WRA) are used to identify plant invaders before introduction. Unfortunately, very few incorporate uncertainty ratings or evaluate the effects of uncertainty, a fundamental risk component. We developed a probabilistic model to quantitatively evaluate the effects of uncertainty on the outcomes of a question-based WRA tool for the United States. In our tool, the uncertainty of each response is rated as Negligible, Low, Moderate, or High. We developed the model by specifying the likelihood of a response changing for each uncertainty rating. The simulations determine if responses change, select new responses, and sum the scores to determine the risk rating. The simulated scores reveal potential variation in WRA risk ratings. In testing with 204 species assessments, the ranges of simulated risk scores increased with greater uncertainty, and analyses for most species produced simulated risk ratings that differed from the baseline WRA rating. Still, the most frequent simulated rating matched the baseline rating for every High Risk species, and for 87% of all tested species. The remaining 13% primarily involved ambiguous Low Risk results. Changing final ratings based on the uncertainty analysis results was not justified here because accuracy (match between WRA tool and known risk rating) did not improve. Detailed analyses of three species assessments indicate that assessment uncertainty may be best reduced by obtaining evidence for unanswered questions, rather than obtaining additional evidence for questions with responses. This analysis represents an advance in interpreting WRA results, and has enhanced our regulation and management of potential weed species.

Communicating Zika Risk: Using Metaphor to Increase Perceived Risk Susceptibility

27 February 2018 - 9:25pm
Abstract

Effectively communicating the risks associated with emerging zoonotic diseases remains an important challenge. Drawing on research into the psychological effects of metaphoric framing, we explore the conditions under which exposure to the “nation as a body” metaphor influences perceived risk susceptibility, behavioral intentions, and policy support in the context of Zika virus. In a between-subjects experiment, 354 U.S. adults were randomly assigned to one of four experimental conditions as part of a 2 (severity message: high vs. low) × 2 (U.S. framing: metaphoric vs. literal) design. Results revealed an interaction effect such that metaphoric (vs. literal) framing increased perceived risk susceptibility in the high-severity condition only. Further analyses revealed that perceived risk susceptibility and negative affect mediated the path between the two-way interaction and policy support and behavioral intentions regarding Zika prevention. Overall, these findings complement prior work on the influence of metaphoric framing on risk perceptions, while offering practical insights for risk communicators seeking to communicate about Zika and other zoonotic diseases.

Risk Assessment and Risk Governance of Liquefied Natural Gas Development in Gladstone, Australia

26 February 2018 - 8:15pm
Abstract

This article is a retrospective analysis of liquefied natural gas development (LNG) in Gladstone, Australia by using the structure of the risk governance framework developed by the International Risk Governance Council (IRGC). Since 2010 the port of Gladstone has undergone extensive expansion to facilitate the increasing coal export as well as the new development of three recently completed LNG facilities. Significant environmental and socio-economic impacts and concerns have occurred as a result of these developments. The overall aim of the article, therefore, is to identify the risk governance deficits that arose and to formulate processes capable of improving similar decision-making problems in the future. The structure of the IRGC framework is followed because it represents a broad analytical approach for considering risk assessment and risk governance in Gladstone in ways that include, but also go beyond, the risk approach of the ISO 31000:2009 standard that was employed at the time. The IRGC risk framework is argued to be a consistent and comprehensive risk governance framework that integrates scientific, economic, social, and cultural aspects and advocates the notion of inclusive risk governance through stakeholder communication and involvement. Key aspects related to risk preassessment, risk appraisal, risk tolerability and acceptability, risk management, and stakeholder communication and involvement are considered. The results indicate that the risk governance deficits include aspects related to (i) the risk matrix methodology, (ii) reflecting uncertainties, (iii) cumulative risks, (iv) the regulatory process, and (v) stakeholder communication and involvement.

How to Perform an Ethical Risk Analysis (eRA)

26 February 2018 - 8:15pm
Abstract

Ethical analysis is often needed in the preparation of policy decisions on risk. A three-step method is proposed for performing an ethical risk analysis (eRA). In the first step, the people concerned are identified and categorized in terms of the distinct but compatible roles of being risk-exposed, a beneficiary, or a decisionmaker. In the second step, a more detailed classification of roles and role combinations is performed, and ethically problematic role combinations are identified. In the third step, further ethical deliberation takes place, with an emphasis on individual risk-benefit weighing, distributional analysis, rights analysis, and power analysis. Ethical issues pertaining to subsidiary risk roles, such as those of experts and journalists, are also treated in this phase. An eRA should supplement, not replace, a traditional risk analysis that puts emphasis on the probabilities and severities of undesirable events but does not cover ethical issues such as agency, interpersonal relationships, and justice.

Resilience Analysis of a Remote Offshore Oil and Gas Facility for a Potential Hydrocarbon Release

15 February 2018 - 9:16am
Abstract

Resilience is the capability of a system to adjust its functionality during a disturbance or perturbation. The present work attempts to quantify resilience as a function of reliability, vulnerability, and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and perturbation. This article employs a Bayesian network format to build a resilience model. The application of the model is tested on hydrocarbon-release scenarios during an offloading operation in a remote and harsh environment. The model identifies requirements for robust recovery and adaptability during an unplanned scenario related to a hydrocarbon release. This study attempts to relate the resilience capacity of a system to the system's absorptive, adaptive, and restorative capacities. These factors influence predisaster and postdisaster strategies that can be mapped to enhance the resilience of the system.

Variability in Cross-Domain Risk Perception among Smallholder Farmers in Mali by Gender and Other Demographic and Attitudinal Characteristics

15 February 2018 - 9:16am
Abstract

Previous research has shown that men and women, on average, have different risk attitudes and may therefore see different value propositions in response to new opportunities. We use data from smallholder farm households in Mali to test whether risk perceptions differ by gender and across domains. We model this potential association across six risks (work injury, extreme weather, community relationships, debt, lack of buyers, and conflict) while controlling for demographic and attitudinal characteristics. Factor analysis highlights extreme weather and conflict as eliciting the most distinct patterns of participant response. Regression analysis for Mali as a whole reveals an association between gender and risk perception, with women expressing more concern except in the extreme weather domain; however, the association with gender is largely absent when models control for geographic region. We also find lower risk perception associated with an individualistic and/or fatalistic worldview, a risk-tolerant outlook, and optimism about the future, while education, better health, a social orientation, self-efficacy, and access to information are generally associated with more frequent worry—with some inconsistency. Income, wealth, and time poverty exhibit complex associations with perception of risk. Understanding whether and how men's and women's risk preferences differ, and identifying other dominant predictors such as geographic region and worldview, could help development organizations to shape risk mitigation interventions to increase the likelihood of adoption, and to avoid inadvertently making certain subpopulations worse off by increasing the potential for negative outcomes.

Issue Information - TOC

7 February 2018 - 7:03am

From the Editors

7 February 2018 - 7:03am

Toward an Application Guide for Safety Integrity Level Allocation in Railway Systems

2 February 2018 - 5:20am
Abstract

The work in the article presents the development of an application guide based on feedback and comments stemming from various railway actors on their practices of SIL allocation to railway safety-related functions. The initial generic methodology for SIL allocation has been updated to be applied to railway rolling stock safety-related functions in order to solve the SIL concept application issues. Various actors dealing with railway SIL allocation problems are the intended target of the methodology; its principles will be summarized in this article with a focus on modifications and precisions made in order to establish a practical guide for railway safety authorities. The methodology is based on the flowchart formalism used in CSM (common safety method) European regulation. It starts with the use of quantitative safety requirements, particularly tolerable hazard rates (THR). THR apportioning rules are applied. On the one hand, the rules are related to classical logical combinations of safety-related functions preventing hazard occurrence. On the other hand, to take into account technical conditions (last safety weak link, functional dependencies, technological complexity, etc.), specific rules implicitly used in existing practices are defined for readjusting some THR values. SIL allocation process based on apportioned and validated THR values is finally illustrated through the example of “emergency brake” subsystems. Some specific SIL allocation rules are also defined and illustrated.

Understanding Fear of Zika: Personal, Interpersonal, and Media Influences

2 February 2018 - 5:20am
Abstract

Fear of infectious disease often motivates people to protect themselves. But, it can also produce negative bio-social-psychological effects whose severity is on par with those of the disease. The WHO declaration of Zika as a world health crisis presented an opportunity to study factors that bring about fear. Beginning nine days after the WHO announcement, data were gathered from women aged 18–35 living in the southern United States (N = 719). Respondents reported experiencing fear of Zika at levels akin to those reported following other significant crises/disasters (e.g., the terrorist attacks of 9/11). Fear increased as a function of (1) personal, but not other-relevance, (2) frequency of media exposure, but not media content, and (3) frequency of interpersonal exposure and interpersonal content. It is argued that media and interpersonal message sources may be innately predisposed to amplify, rather than attenuate, risk.

On the Relationship between Safety and Decision Significance

31 January 2018 - 10:26am
Abstract

Risk analysts are often concerned with identifying key safety drivers, that is, the systems, structures, and components (SSCs) that matter the most to safety. SSCs importance is assessed both in the design phase (i.e., before a system is built) and in the implementation phase (i.e., when the system has been built) using the same importance measures. However, in a design phase, it would be necessary to appreciate whether the failure/success of a given SSC can cause the overall decision to change from accept to reject (decision significance). This work addresses the search for the conditions under which SSCs that are safety significant are also decision significant. To address this issue, the work proposes the notion of a θ-importance measure. We study in detail the relationships among risk importance measures to determine which properties guarantee that the ranking of SSCs does not change before and after the decision is made. An application to a probabilistic safety assessment model developed at NASA illustrates the risk management implications of our work.

Mitigating Litigating: An Examination of Psychosocial Impacts of Compensation Processes Associated with the 2010 BP Deepwater Horizon Oil Spill

31 January 2018 - 10:25am
Abstract

During the past four decades, a number of social science scholars have conceptualized technological disasters as a social problem. More specifically, research in this arena has identified individual and collective stress as a secondary trauma of processes intended to provide compensation and economic relief from disasters in general and, more specifically, technological disasters. Based on data from a 2013 household telephone survey of 1,216 residents of coastal Alabama, this article examines the relationship between psychosocial stress and compensation processes related to the 2010 BP Deepwater Horizon oil spill. We examine involvement with claims, settlement, and litigation activities; vulnerability and exposure to the spill; ties to resources; resource loss and gain; perceptions of risk and recreancy; and intrusive stress and avoidance behaviors as measured by the impact of event scale. Regression analysis reveals that the strongest contributors to intrusive stress were being part of the compensation process, resource loss, concerns about air quality, and income. Although being involved with compensation processes was a significant predictor of avoidance behaviors, the strongest contributors to avoidance behaviors were resource loss, air quality concern, income, being male, minority status, and community attachment. Beliefs that the compensation process was as distressing as the oil spill also significantly contributed to intrusive stress and avoidance behaviors. This research represents a step toward filling a gap in empirical evidence regarding the extent to which protracted compensation processes exacerbate adverse psychosocial impacts of disasters and hinder community recovery.

A Comprehensive Risk Analysis of Transportation Networks Affected by Rainfall-Induced Multihazards

26 January 2018 - 8:35pm
Abstract

Climate change and its projected natural hazards have an adverse impact on the functionality and operation of transportation infrastructure systems. This study presents a comprehensive framework to analyze the risk to transportation infrastructure networks that are affected by natural hazards. The proposed risk analysis method considers both the failure probability of infrastructure components and the expected infrastructure network efficiency and capacity loss due to component failure. This comprehensive approach facilitates the identification of high-risk network links in terms of not only their susceptibility to natural hazards but also their overall impact on the network. The Chinese national rail system and its exposure to rainfall-related multihazards are used as a case study. The importance of various links is comprehensively assessed from the perspectives of topological, efficiency, and capacity criticality. Risk maps of the national railway system are generated, which can guide decisive action regarding investments in preventative and adaptive measures to reduce risk.

Lognormal Approximations of Fault Tree Uncertainty Distributions

26 January 2018 - 8:35pm
Abstract

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks’s method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models.

Pages