Risk Analysis

Publisher: Society for Risk Analysis, Wiley

Journal description

Current impact factor: 1.97

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 1.974
2012 Impact Factor 2.278
2011 Impact Factor 2.366
2010 Impact Factor 2.096
2009 Impact Factor 1.953
2008 Impact Factor 1.831
2007 Impact Factor 1.784
2006 Impact Factor 1.938
2005 Impact Factor 1.51
2004 Impact Factor 1.321
2003 Impact Factor 1.064

Impact factor over time

Impact factor
Year

Additional details

5-year impact 2.47
Cited half-life 8.50
Immediacy index 0.78
Eigenfactor 0.01
Article influence 0.86
Other titles Risk analysis (Online), Risk analysis
ISSN 1539-6924
OCLC 45175725
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Wiley

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • 2 years embargo
  • Conditions
    • Some journals have separate policies, please check with each journal directly
    • On author's personal website, institutional repositories, arXiv, AgEcon, PhilPapers, PubMed Central, RePEc or Social Science Research Network
    • Author's pre-print may not be updated with Publisher's Version/PDF
    • Author's pre-print must acknowledge acceptance for publication
    • On a non-profit server
    • Publisher's version/PDF cannot be used
    • Publisher source must be acknowledged with citation
    • Must link to publisher version with set statement (see policy)
    • If OnlineOpen is available, BBSRC, EPSRC, MRC, NERC and STFC authors, may self-archive after 12 months
    • If OnlineOpen is available, AHRC and ESRC authors, may self-archive after 24 months
    • Publisher last contacted on 07/08/2014
    • This policy is an exception to the default policies of 'Wiley'
  • Classification
    ​ yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Recent findings on construal level theory (CLT) suggest that abstract thinking leads to a lower estimated probability of an event occurring compared to concrete thinking. We applied this idea to the risk context and explored the influence of construal level (CL) on the overestimation of small and underestimation of large probabilities for risk estimates concerning a vague target person (Study 1 and Study 3) and personal risk estimates (Study 2). We were specifically interested in whether the often-found overestimation of small probabilities could be reduced with abstract thinking, and the often-found underestimation of large probabilities was reduced with concrete thinking. The results showed that CL influenced risk estimates. In particular, a concrete mindset led to higher risk estimates compared to an abstract mindset for several adverse events, including events with small and large probabilities. This suggests that CL manipulation can indeed be used for improving the accuracy of lay people's estimates of small and large probabilities. Moreover, the results suggest that professional risk managers' risk estimates of common events (thus with a relatively high probability) could be improved by adopting a concrete mindset. However, the abstract manipulation did not lead managers to estimate extremely unlikely events more accurately. Potential reasons for different CL manipulation effects on risk estimates' accuracy between lay people and risk managers are discussed. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12445
  • Kimberly M Thompson, Kasper H Kisjes
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    ABSTRACT: Measles outbreaks in the United States continue to occur in subpopulations with sufficient numbers of undervaccinated individuals, with a 2014 outbreak in Amish communities in Ohio pushing the annual cases to the highest national number reported in the last 20 years. We adapted an individual-based model developed to explore potential poliovirus transmission in the North American Amish to characterize a 1988 measles outbreak in the Pennsylvania Amish and the 2014 outbreak in the Ohio Amish. We explored the impact of the 2014 outbreak response compared to no or partial response. Measles can spread very rapidly in an underimmunized subpopulation like the North American Amish, with the potential for national spread within a year or so in the absence of outbreak response. Vaccination efforts significantly reduced the transmission of measles and the expected number of cases. Until global eradication, measles importations will continue to pose a threat to clusters of underimmunized individuals in the United States. Aggressive outbreak response efforts in Ohio probably prevented widespread transmission of measles within the entire North American Amish. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12440
  • [Show abstract] [Hide abstract]
    ABSTRACT: To estimate the effects of a policy change, analysts must often rely on available data as time and resource constraints limit their ability to commission new primary research. Research synthesis methods-including systematic review, meta-analysis, and expert elicitation-play an important role in ensuring that this evidence is appropriately weighed and considered. We present the conclusions of a multidisciplinary Harvard Center for Risk Analysis project that evaluated and applied these methods, and introduce the resulting series of articles. The first step in any analysis is to clearly define the problem to be addressed; the second is a systematic review of the literature. Whether additional analysis is needed depends on the quality and relevance of the available data to the policy question, and the likely effect of uncertainty on the policy decision. Meta-analysis promotes understanding the variation between studies and may be used to combine the estimates to develop values for application in policy analysis. Formal, structured expert elicitation promotes careful consideration of the evidence when data are limited or inconsistent, and aids in extrapolating to the policy context. Regardless of the methods used, clear communication of the approach, assumptions, and uncertainty is essential. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12437
  • [Show abstract] [Hide abstract]
    ABSTRACT: Serological tests provide information about individual immunity from historical infection or immunization. Cross-sectional serological studies provide data about the age- and sex-specific immunity levels for individuals in the studied population, and these data can provide a point of comparison for the results of transmission models. In the context of developing an integrated model for measles and rubella transmission, we reviewed the existing measles and rubella literature to identify the results of national serological studies that provided cross-sectional estimates of population immunity at the time of data collection. We systematically searched PubMed, the Science Citation Index, and references we identified from relevant articles published in English. We extracted serological data for comparison to transmission model outputs. For rubella, serological studies of women of child-bearing age provide information about the potential risks of infants born with congenital rubella syndrome. Serological studies also document the loss of maternal antibodies, which occurs at different rates for the different viruses and according to the nature of the induced immunity (i.e., infection or vaccine). The serological evidence remains limited for some areas, with studies from developed countries representing a disproportionate part of the evidence. The collection and review of serological evidence can help program managers identify immunity gaps in the population, which may help them better understand the characteristics of individuals within their populations who may participate in transmission and manage risks. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12430
  • [Show abstract] [Hide abstract]
    ABSTRACT: This article focuses on the fluid nature of risk problems and the challenges it presents to establishing acceptability in risk governance. It introduces an actor-network theory (ANT) perspective as a way to deal with the mutable nature of risk controversies and the configuration of stakeholders. To translate this into a practicable framework, the article proposes a hybrid risk governance framework that combines ANT with integrative risk governance, deliberative democracy, and responsive regulation. This addresses a number of the limitations in existing risk governance models, including: (1) the lack of more substantive public participation throughout the lifecycle of a project; (2) hijacking of deliberative forums by particular groups; and (3) the treatment of risk problems and their associated stakeholders as immutable entities. The framework constitutes a five-stage process of co-selection, co-design, co-planning, and co-regulation to facilitate the co-production of collective interests and knowledge, build capacities, and strengthen accountability in the process. The aims of this article are twofold: conceptually, it introduces a framework of risk governance that accounts for the mutable nature of risk problems and configuration of stakeholders. In practice, this article offers risk managers and practitioners of risk governance a set of procedures with which to operationalize this conceptual approach to risk and stakeholder engagement. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12429
  • [Show abstract] [Hide abstract]
    ABSTRACT: Current risk assessment guidance calls for an individual chemical-by-chemical approach that fails to capture potential interactive effects of exposure to environmental mixtures and genetic variability. We conducted a review of the literature on relationships between prenatal and early life exposure to mixtures of lead (Pb), arsenic (As), cadmium (Cd), and manganese (Mn) with neurodevelopmental outcomes. We then used an adverse outcome pathway (AOP) framework to integrate lines of evidence from multiple disciplines based on evolving guidance developed by the Organization for Economic Cooperation and Development (OECD). Toxicological evidence suggests a greater than additive effect of combined exposures to As-Pb-Cd and to Mn with any other metal, and several epidemiologic studies also suggest synergistic effects from binary combinations of Pb-As, Pb-Cd, and Pb-Mn. The exposure levels reported in these epidemiologic studies largely fall at the high-end (e.g., 95th percentile) of biomonitoring data from the National Health and Nutrition Examination Survey (NHANES), suggesting a small but significant potential for high-end exposures. This review integrates multiple data sources using an AOP framework and provides an initial application of the OECD guidance in the context of potential neurodevelopmental toxicity of several metals, recognizing the evolving nature of regulatory interpretation and acceptance. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12425
  • [Show abstract] [Hide abstract]
    ABSTRACT: We present a risk analysis undertaken to mitigate problems in relation to the unintended deployment of slides under normal operations within a commercial airline. This type of incident entails relevant costs for the airline industry. After assessing the likelihood and severity of its consequences, we conclude that such risks need to be managed. We then evaluate the effectiveness of various countermeasures, describing and justifying the chosen ones. We also discuss several issues faced when implementing and communicating the proposed measures, thus fully illustrating the risk analysis process. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12428
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recently, there has been considerable interest in developing risk-based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk-based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz () laid the foundation for modern portfolio theory based on mean-variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false "optimal" portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out-of-sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk-based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers. © 2015 Society for Risk Analysis.
    Risk Analysis 06/2015; DOI:10.1111/risa.12415
  • [Show abstract] [Hide abstract]
    ABSTRACT: Many health-related decisions require choosing between two options, each with risks and benefits. When presented with such tradeoffs, people often make choices that fail to align with scientific evidence or with their own values. This study tested whether risk communication and values clarification methods could help parents and guardians make evidence-based, values-congruent decisions about children's influenza vaccinations. In 2013-2014 we conducted an online 2×2 factorial experiment in which a diverse sample of U.S. parents and guardians (n = 407) were randomly assigned to view either standard information about influenza vaccines or risk communication using absolute and incremental risk formats. Participants were then either presented or not presented with an interactive values clarification interface with constrained sliders and dynamic visual feedback. Participants randomized to the risk communication condition combined with the values clarification interface were more likely to indicate intentions to vaccinate (β = 2.10, t(399) = 2.63, p < 0.01). The effect was particularly notable among participants who had previously demonstrated less interest in having their children vaccinated against influenza (β = -2.14, t(399) = -2.06, p < 0.05). When assessing vaccination status reported by participants who agreed to participate in a follow-up study six months later (n = 116), vaccination intentions significantly predicted vaccination status (OR = 1.66, 95%CI (1.13, 2.44), p < 0.05) and rates of informed choice (OR = 1.51, 95%CI (1.07, 2.13), p < 0.012), although there were no direct effects of experimental factors on vaccination rates. Qualitative analysis suggested that logistical barriers impeded immunization rates. Risk communication and values clarification methods may contribute to increased vaccination intentions, which may, in turn, predict vaccination status if logistical barriers are also addressed. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12418
  • [Show abstract] [Hide abstract]
    ABSTRACT: The U.S. federal government regulates the reliability of bulk power systems, while the reliability of power distribution systems is regulated at a state level. In this article, we review the history of regulating electric service reliability and study the existing reliability metrics, indices, and standards for power transmission and distribution networks. We assess the foundations of the reliability standards and metrics, discuss how they are applied to outages caused by large exogenous disturbances such as natural disasters, and investigate whether the standards adequately internalize the impacts of these events. Our reflections shed light on how existing standards conceptualize reliability, question the basis for treating large-scale hazard-induced outages differently from normal daily outages, and discuss whether this conceptualization maps well onto customer expectations. We show that the risk indices for transmission systems used in regulating power system reliability do not adequately capture the risks that transmission systems are prone to, particularly when it comes to low-probability high-impact events. We also point out several shortcomings associated with the way in which regulators require utilities to calculate and report distribution system reliability indices. We offer several recommendations for improving the conceptualization of reliability metrics and standards. We conclude that while the approaches taken in reliability standards have made considerable advances in enhancing the reliability of power systems and may be logical from a utility perspective during normal operation, existing standards do not provide a sufficient incentive structure for the utilities to adequately ensure high levels of reliability for end-users, particularly during large-scale events. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12401
  • [Show abstract] [Hide abstract]
    ABSTRACT: Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure-ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose-response approach, (6) dose-response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12414
  • [Show abstract] [Hide abstract]
    ABSTRACT: We describe recent advances in biophysical and social aspects of risk and their potential combined contribution to improve mitigation planning on fire-prone landscapes. The methods and tools provide an improved method for defining the spatial extent of wildfire risk to communities compared to current planning processes. They also propose an expanded role for social science to improve understanding of community-wide risk perceptions and to predict property owners' capacities and willingness to mitigate risk by treating hazardous fuels and reducing the susceptibility of dwellings. In particular, we identify spatial scale mismatches in wildfire mitigation planning and their potential adverse impact on risk mitigation goals. Studies in other fire-prone regions suggest that these scale mismatches are widespread and contribute to continued wildfire dwelling losses. We discuss how risk perceptions and behavior contribute to scale mismatches and how they can be minimized through integrated analyses of landscape wildfire transmission and social factors that describe the potential for collaboration among landowners and land management agencies. These concepts are then used to outline an integrated socioecological planning framework to identify optimal strategies for local community risk mitigation and improve landscape-scale prioritization of fuel management investments by government entities. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12373
  • [Show abstract] [Hide abstract]
    ABSTRACT: A model for the transmission of Salmonella between finisher pigs during transport to the abattoir and subsequent lairage has been developed, including novel factors such as environmental contamination and the effect of stress, and is designed to be adaptable for any EU Member State (MS). The model forms part of a generic farm-to-consumption model for Salmonella in pigs, designed to model potentially important risk factors and assess the effectiveness of interventions. In this article, we discuss the parameterization of the model for two case study MSs. For both MSs, the model predicted an increase in the average MS-level prevalence of Salmonella-positive pigs during both transport and lairage, accounting for a large amount of the variation between reported on-farm prevalence and reported lymph-node prevalence at the slaughterhouse. Sensitivity analysis suggested that stress is the most important factor during transport, while a number of factors, including environmental contamination and the dose-response parameters, are important during lairage. There was wide variation in the model-predicted change in prevalence in individual batches; while the majority of batches (80-90%) had no increase, in some batches the increase in prevalence was over 70% and in some cases infection was introduced into previously uninfected batches of pigs. Thus, the model suggests that while the transport and lairage stages of the farm-to-consumption exposure pathway are unlikely to be responsible for a large increase in average prevalence at the MS level, they can have a large effect on prevalence at an individual-batch level. © 2015 Society for Risk Analysis.
    Risk Analysis 05/2015; DOI:10.1111/risa.12390