From the Editors

This issue begins with two articles that address questions of fundamental importance for applied risk analysis. Charles Vlek asks: How can governments best evaluate major hazards and threats in their countries to support fair, efficient, and effective priorities for limited safety investments? After scrutinizing the soundness of national risk assessments (NRAs) based on scenarios, expert judgments, risk matrices and rankings, and related concepts and tools, he recommends better external review and better validation of NRA components to strengthen the reliability of results. USDA's Mark Powell examines the vexed question: What should be considered “negligible” probability? In the applied context of World Trade Organization (WTO) Dispute Settlement Panel deliberations, can negligible probability be represented adequately by a uniform distribution between 0 and some small number (e.g., 1 in a million), or should triangular (or other) uncertainty distributions be required? Powell shows that the choice makes little practical difference in a dispute over an Australian Import Risk Analysis for apples imported from New Zealand, and reflects on the potential implications of this case study for the standard of review for risk assessments under the WTO Sanitary and Phytosanitary (SPS) Agreement. Several articles in this issue address aspects of natural disaster risk management. Michel-Kerjan and co-authors note the huge and growing human and economic costs of disaster relief, especially in developing countries. They show how to develop cost-benefit analyses and identify the most effective DRR measures using advanced probabilistic catastrophe models, with modules representing hazard (via stochastic simulation models of event frequencies and severities), exposure, vulnerability, and average annual loss. Two articles address risk analysis of wildfires. Ager et al. apply simulation modeling and spatial data from geographic information systems to identify how spatial variations in burn probabilities and probable extents of wildfires might be used to improve prioritization of wildfire risk reduction and preparedness investments in the Pacific Northwest. Wibbenmeyer et al. investigate the risk and decision preferences of U.S. federal wildfire managers, based on their responses to a choice experiment questionnaire, and conclude that manager decisions may depart from the prescriptions of rational (expected utility) and effective decision making, e.g., by overresponding to relatively small (unlikely or low-damage) fire threats. Three articles address issues of risk perception. Earlier work by Slovic and colleagues demonstrated that perceptions of risks and benefits for nuclear power (and other technologies and activities) tend to be negatively correlated, due to the affect heuristic. Roman Seidl et al. note that much previous research on polarized perceptions of risk-benefit combinations has focused mainly on the perceptions of proponents and opponents, paying less attention to the perceptions of the majority of people who have ambivalent opinions (perceiving both high risks and high benefits), or who are indifferent (perceiving both risks and benefits as low). Yet, all four preference patterns are evident in the responses of German-speaking Swiss to a mail survey about perceptions of nuclear waste repositories. Better understanding of the perceptions of those with ambivalent or indifferent, rather than extreme, perceptions, and of the stability of these perceptual clusters over time and in light of new information may help to illuminate the dynamics of shifting public opinions and possibilities for conflict resolution of contentious risk management issues (such as acceptance of proposed nuclear waste repositories). Wachinger et al. review literature on risk perception of natural hazards, and examine the apparent paradox that those who report the greatest perceptions of risk are not necessarily those who prepare themselves best to mitigate the perceived risks. Instead, behavior in response to perceived risks depends on trust in authority and in one's self to take effective protective action if the need arises. Understanding such mediating factors can improve risk communication and governance for both natural hazards and complex hazards perceived as arising from a combination of natural and technological causes. Cao and McGill consider how to use fun games, in which pairs of players (including some bots) solve puzzles, to engage participants in spontaneously revealing information about what they know and think about risks. Player responses can be mapped to influence diagram representations of group mental models and used to design risk communication materials to inform perceptions about risks and their drivers. Top-down allocation of resources to local opportunities for risk reduction raises political issues and fairness concerns as local interests vie for funding. Shan and Zhuang consider the allocation of homeland security resources among potential targets, taking into account both that intelligent adversaries adapt their attack probabilities based on defensive resource allocations, and that political pressures (often criticized as “pork barrel politics”) and concerns for equity push for each area to receive some of the available funding. They compare five types of funding equity (e.g., per-target, per-capita, per-density-weighted population size, etc.) and quantify the tradeoff between increasing equity of resource allocation and increasing expected property loss, assuming that defensive and attack resources are each allocated optimally, given the equity constraints. Risk model verification, validation, and quantification of uncertainty and variability are central parts of the risk practitioner's craft. They are advanced in this issue via articles on food safety, combination of expert opinions, nuclear power plant safety, and uncertainties in fault tree modeling. Smid et al. develop a Bayesian network model to combine uncertainty within an experiment, variability across experiments, and constraints on realistic values to characterize the transfer ratio of Salmonella bacteria from pork meat to a butcher's knife, and from the knife to other meat. Baker and Olaleye consider how to combine expert opinions about the product of two probabilities (e.g., the product of the probability of developing a solar cell with an efficiency of at least x% and the conditional probability of it costing no more than $y per square meter, given that its efficiency is at least x%). They compare two procedures: average the experts’ judgments about each component probability, and then multiply these averages; or average expert judgments about the joint probability (i.e., the product of the two component probabilities). These may yield different conclusions (e.g., if Expert 1 assesses probabilities of 0 and 1 for events A and B, and Expert 2 assesses probabilities of 1 and 0, then averaging and multiplying would yield an estimated product of 0.5 * 0.5 = 0.25, but multiplying and averaging would yield an estimated product of 0 * 0 = 0). Baker and Olaleye conclude that the former procedure leads to smaller expected errors and variances than the latter when expert opinions are related to underlying true probabilities by a simple model with additive errors, although the difference may be small in practice. Rastogi and Gabbar present a real-time safety verification framework for nuclear power plants, in which quantitative risk estimates for different plant processes are compared to safety and control limits in real time to verify ongoing operation within safe limits. Case studies demonstrate that the required calculations and comparisons can be carried out in practice in real time, using fuzzy logic to implement easily computed safety rules. Pedroni and Zio compare the effects on estimated probabilities of top events in fault trees (e.g., a system failure or catastrophic accident) of two types of uncertainty that can create dependencies among the basic events (e.g., failures of individual components): epistemic uncertainties due to limited knowledge, and aleatory uncertainties due to stochastic (random) behaviors of devices or occurrences of basic events. Working within an uncertainty analysis framework that combines possibility distributions, Dempster-Shafer belief functions, and probability distributions, they find that objective (aleatory) dependencies among basic events linked by AND gates can increase the estimated risks of top events significantly, implying that conservative risk estimates require considering the possibility of such dependencies, even if they are not known with certainty to exist. Special Note from EIC: This is my first issue as EIC. I am honored and delighted to have the opportunity to work with our outstanding Editorial Board members, authors, and reviewers to take Risk Analysis to the next level. I join many in the SRA community in warmly thanking Michael Greenberg, our previous EIC, for a job outstandingly done. Mike leaves us a healthy, successful, and impactful journal with a strong pipeline of articles and an active community of contributors and readers. He will stay closely involved with Risk Analysis, heading an Advisory Board, at my request, that will consider how to expand the reach, impact, circulation, and practical and intellectual contributions of our journal. Many thanks and congratulations, Michael! I am grateful to Mike, Karen, the Area Editors and Editorial Board, and our authors and reviewers for such a great legacy on which to build. I look forward to your feedback, suggestions, and thoughts for how we can make a great journal even better!

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