Risk Analysis

Publisher: Society for Risk Analysis, Blackwell Publishing

Description

Impact factor 2.28

  • 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

Blackwell Publishing

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Restrictions
    • Some journals impose embargoes typically of 6 or 12 months, occasionally of 24 months
    • no listing of affected journals available as yet
  • Conditions
    • See Wiley-Blackwell entry for articles after February 2007
    • Publisher's version/PDF cannot be used
    • On author's server, institutional server or subject-based server
    • Server must be non-commercial
    • Publisher copyright and source must be acknowledged with set statement ("The definitive version is available at www.blackwell-synergy.com")
    • Articles in some journals can be made Open Access on payment of additional charge
    • 'Blackwell Publishing' is an imprint of 'Wiley'
  • Classification
    ​ yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed.For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20–22 orders of magnitude.Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.
    Risk Analysis 01/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: The Flood Risk in the Netherlands project (Dutch acronym: VNK2) is a large-scale probabilistic risk assessment for all major levee systems in the Netherlands. This article provides an overview of the methods and techniques used in the VNK2 project. It also discusses two examples that illustrate the potential of quantitative flood risk assessments such as VNK2 to improve flood risk management processes: (i) informing political debates about the risks of flooding and the effectiveness of risk management actions, and (ii) (re)directing research efforts towards important sources of uncertainty.
    Risk Analysis 01/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Although risk and benefits of risky activities are positively correlated in real world, empirical results indicate that people perceive them as negatively correlated. The common explanation is that confounding benefits and losses stems from affect. In this article, we address an issue that has not been clearly established in studies on the affect heuristic: to what extent boundary conditions, such as judgments’ generality and expertise influence the presence of the inverse relation in judgments of hazards. These conditions were examined in four studies in which respondents evaluated general or specific benefits and risks of “affect-rich” and “affect-poor” hazards (ranging from investments to applications of stem cell research). In line with previous research, affect is defined as good or bad feelings integral to a stimulus. In contrast to previous research, affect is considered as related both to personal feelings and to social controversies associated with a hazard. Expertise is related to personal knowledge (laypersons vs. experts) as well as to objective knowledge (targets well vs. poorly known to science). The direct comparison of the input from personal and objective ignorance into the inverse relation has not been investigated previously. It was found that affect invoked by a hazard guides general but not specific judgments of its benefits and risks. Technical expertise helps to avoid simplified evaluations of consequences as long as they are well known to science. For new, poorly understood hazards (e.g. stem cell research), expertise does not protect from the perception of the inverse relation between benefits and risks.
    Risk Analysis 01/2015; fprthcomming.
  • [Show abstract] [Hide abstract]
    ABSTRACT: A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed.
    Risk Analysis 01/2015;
  • Jared LeClerc, Susan Joslyn
    [Show abstract] [Hide abstract]
    ABSTRACT: Despite improvements in forecasting extreme weather events, noncompliance with weather warnings among the public remains a problem. Although there are likely many reasons for noncompliance with weather warnings, one important factor might be people's past experiences with false alarms. The research presented here explores the role of false alarms in weather-related decision making. Over a series of trials, participants used an overnight low temperature forecast and advice from a decision aid to decide whether to apply salt treatment to a town's roads to prevent icy conditions or take the risk of withholding treatment, which resulted in a large penalty when freezing temperatures occurred. The decision aid gave treatment recommendations, some of which were false alarms, i.e., treatment was recommended but observed temperatures were above freezing. The rate at which the advice resulted in false alarms was manipulated between groups. Results suggest that very high and very low false alarm rates led to inferior decision making, but that lowering the false alarm rate slightly did not significantly affect compliance or decision quality. However, adding a probabilistic uncertainty estimate in the forecasts improved both compliance and decision quality. These findings carry implications about how weather warnings should be communicated to the public.
    Risk Analysis 01/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Perceptions of institutions that manage hazards are important because they can affect how the public responds to hazard events. Antecedents of trust judgments have received far more attention than antecedents of attributions of responsibility for hazard events. We build upon a model of retrospective attribution of responsibility to individuals to examine these relationships regarding five classes of institutions that bear responsibility for food safety: producers (e.g., farmers), processors (e.g., packaging firms), watchdogs (e.g., government agencies), sellers (e.g., supermarkets), and preparers (e.g., restaurants). A nationally representative sample of 1,200 American adults completed an Internet-based survey in which a hypothetical scenario involving contamination of diverse foods with Salmonella served as the stimulus event. Perceived competence and good intentions of the institution moderately decreased attributions of responsibility. A stronger factor was whether an institution was deemed (potentially) aware of the contamination and free to act to prevent or mitigate it. Responsibility was rated higher the more aware and free the institution. This initial model for attributions of responsibility to impersonal institutions (as opposed to individual responsibility) merits further development. © 2014 Society for Risk Analysis.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: A game-theoretic model is developed where an infrastructure of N targets is protected against terrorism threats. An original threat score is determined by the terrorist's threat against each target and the government's inherent protection level and original protection. The final threat score is impacted by the government's additional protection. We investigate and verify the effectiveness of countermeasures using empirical data and two methods. The first is to estimate the model's parameter values to minimize the sum of the squared differences between the government's additional resource investment predicted by the model and the empirical data. The second is to develop a multivariate regression model where the final threat score varies approximately linearly relative to the original threat score, sectors, and threat scenarios, and depends nonlinearly on the additional resource investment. The model and method are offered as tools, and as a way of thinking, to determine optimal resource investments across vulnerable targets subject to terrorism threats. © 2014 Society for Risk Analysis.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Since motor vehicles are a major air pollution source, urban designs that decrease private automobile use could improve air quality and decrease air pollution health risks. Yet, the relationships among urban form, air quality, and health are complex and not fully understood. To explore these relationships, we model the effects of three alternative development scenarios on annual average fine particulate matter (PM2.5 ) concentrations in ambient air and associated health risks from PM2.5 exposure in North Carolina's Raleigh-Durham-Chapel Hill area. We integrate transportation demand, land-use regression, and health risk assessment models to predict air quality and health impacts for three development scenarios: current conditions, compact development, and sprawling development. Compact development slightly decreases (-0.2%) point estimates of regional annual average PM2.5 concentrations, while sprawling development slightly increases (+1%) concentrations. However, point estimates of health impacts are in opposite directions: compact development increases (+39%) and sprawling development decreases (-33%) PM2.5 -attributable mortality. Furthermore, compactness increases local variation in PM2.5 concentrations and increases the severity of local air pollution hotspots. Hence, this research suggests that while compact development may improve air quality from a regional perspective, it may also increase the concentration of PM2.5 in local hotspots and increase population exposure to PM2.5 . Health effects may be magnified if compact neighborhoods and PM2.5 hotspots are spatially co-located. We conclude that compactness alone is an insufficient means of reducing the public health impacts of transportation emissions in automobile-dependent regions. Rather, additional measures are needed to decrease automobile dependence and the health risks of transportation emissions. © 2014 Society for Risk Analysis.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: A comprehensive methodology for economic consequence analysis with appropriate models for risk analysis of process systems is proposed. This methodology uses loss functions to relate process deviations in a given scenario to economic losses. It consists of four steps: definition of a scenario, identification of losses, quantification of losses, and integration of losses. In this methodology, the process deviations that contribute to a given accident scenario are identified and mapped to assess potential consequences. Losses are assessed with an appropriate loss function (revised Taguchi, modified inverted normal) for each type of loss. The total loss is quantified by integrating different loss functions. The proposed methodology has been examined on two industrial case studies. Implementation of this new economic consequence methodology in quantitative risk assessment will provide better understanding and quantification of risk. This will improve design, decision making, and risk management strategies. © 2014 Society for Risk Analysis.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: The current research proposes that situationally activated anxiety—whether incidental or integral—impairs decision making. In particular, we theorize that anxiety drives decision makers to more heavily emphasize subjective anecdotal information in their decision making, at the expense of more factual statistical information—a deleterious heuristic called the anecdotal bias. Four studies provide consistent support for this assertion. Studies 1A and 1B feature field experiments that demonstrate the role of incidental anxiety in enhancing the anecdotal bias in a choice context. Study 2 builds on these findings, manipulating individuals’ incidental anxiety and showing how this affects the anecdotal bias in the context of message evaluations. Study 2 also provides direct evidence that only high-arousal negative emotions such as anxiety/worry enhance the anecdotal bias, not just any negative emotion (e.g., sadness). While the first three studies examine how incidental anxiety impacts choice, the last study demonstrates the effect of integral anxiety on decision making, manipulating anxiety by intensifying participants’ perceived risk. Our results show that—consistent with findings from our first three studies—the anecdotal bias is enhanced when anxiety is heightened by individuals’ perception of risk.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Prediction of noncancer toxicologic outcomes in rodent bioassays of 37 chemicals from the National Toxicology Program was evaluated. Using the nonneoplastic lesions noted by NTP pathologists, we evaluate both agreement in toxic lesions across experiments and the predictive value of the presence (or absence) of a lesion in one group for other groups. We compare lesions between mice and rats, male mice and male rats, and female mice and female rats in both short-term and long-term bioassays. We also examine whether lesions found in a specific organ in a short-term test are also found in the long-term test of the same chemical. We find agreement (concordance) across species for specific lesions, as evaluated by the Kappa statistic, ranging from 0.58 (for concordance of nasal lesions between female mice and rats in long-term studies) to −0.14 (lung lesions between mice and rats in long-term studies). Predictive values are limited by the relatively small numbers of observations of each type of lesion. Positive predictive values range from 100% to 0%. Comparing the lesions found in short-term tests to those found in long-term tests resulted in Kappa statistic values from 0.76 (spleen lesions in male rats) to −0.61 (lung lesions in female mice). Positive predictive values of short-term tests for long-term tests range from 70% to 0%. Overall, there is considerable uncertainty in predicting the site of toxic lesions in different species exposed to the same chemical and from short-term to long-term tests of the same chemical.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Federal and other regulatory agencies often use or claim to use a weight of evidence (WoE) approach in chemical evaluation. Their approaches to the use of WoE, however, differ significantly, rely heavily on subjective professional judgment, and merit improvement. We review uses of WoE approaches in key articles in the peer-reviewed scientific literature, and find significant variations. We find that a hypothesis-based WoE approach, developed by Lorenz Rhomberg et al., can provide a stronger scientific basis for chemical assessment while improving transparency and preserving the appropriate scope of professional judgment. Their approach, while still evolving, relies on the explicit specification of the hypothesized basis for using the information at hand to infer the ability of an agent to cause human health impacts or, more broadly, affect other endpoints of concern. We describe and endorse such a hypothesis-based WoE approach to chemical evaluation.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Economic analyses for vaccine-preventable diseases provide important insights about the value of prevention. We reviewed the literature to identify all of the peer-reviewed, published economic analyses of interventions related to measles and rubella immunization options to assess the different types of analyses performed and characterize key insights. We searched PubMed, the Science Citation Index, and references from relevant articles for studies in English and found 67 analyses that reported primary data and quantitative estimates of benefit-cost or cost-effectiveness analyses for measles and/or rubella immunization interventions. We removed studies that we characterized as cost-minimization analyses from this sample because they generally provide insights that focused on more optimal strategies to achieve the same health outcome. The 67 analyses we included demonstrate the large economic benefits associated with preventing measles and rubella infections using vaccines and the benefit of combining measles and rubella antigens into a formulation that saves the costs associated with injecting the vaccines separately. Despite the importance of population immunity and dynamic viral transmission, most of the analyses used static models to estimate cases prevented and characterize benefits, although the use of dynamic models continues to increase. Many of the analyses focused on characterizing the most significant adverse outcomes (e.g., mortality for measles, congenital rubella syndrome for rubella) and/or only direct costs, and the most complete analyses present data from high-income countries.
    Risk Analysis 12/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Many risk scholars recognize the importance of including ethical considerations in risk management. Risk ethics can provide in-depth ethical analysis so that ethical considerations can be part of risk-related decisions, rather than an afterthought to those decisions. In this article, I present a brief sketch of the field of risk ethics. I argue that risk ethics has a bias toward technological hazards, thereby overlooking the risks that stem from natural and semi-natural hazards. In order to make a contribution to the field of risk research, risks ethics should broaden its scope to include natural and semi-natural hazards and develop normative distribution criteria that can support decision making on such hazards.
    Risk Analysis 12/2014;
  • Risk Analysis 12/2014; 34(12).
  • [Show abstract] [Hide abstract]
    ABSTRACT: Two forms of single-hit infection dose-response models have previously been developed to assess available data from human feeding trials and estimate the norovirus dose-response relationship. The mechanistic interpretations of these models include strong assumptions that warrant reconsideration: the first study includes an implicit assumption that there is no immunity to Norwalk virus among the specific study population, while the recent second study includes assumptions that such immunity could exist and that the nonimmune have no defensive barriers to prevent infection from exposure to just one virus. Both models addressed unmeasured virus aggregation in administered doses. In this work, the available data are reanalyzed using a generalization of the first model to explore these previous assumptions. It was hypothesized that concurrent estimation of an unmeasured degree of virus aggregation and important dose-response parameters could lead to structural nonidentifiability of the model (i.e., that a diverse range of alternative mechanistic interpretations yield the same optimal fit), and this is demonstrated using the profile likelihood approach and by algebraic proof. It is also demonstrated that omission of an immunity parameter can artificially inflate the estimated degree of aggregation and falsely suggest high susceptibility among the nonimmune. The currently available data support the assumption of immunity within the specific study population, but provide only weak information about the degree of aggregation and susceptibility among the nonimmune. The probability of infection at low and moderate doses may be much lower than previously asserted, but more data from strategically designed dose-response experiments are needed to provide adequate information.
    Risk Analysis 12/2014;