A Multifactorial Risk Prioritization Framework for Foodborne Pathogens

We develop a prioritization framework for foodborne risks that considers public health impact as well as three other factors (market impact, consumer risk acceptance and perception, and social sensitivity). Canadian case studies are presented for six pathogen‐food combinations: Campylobacter spp. in chicken; Salmonella spp. in chicken and spinach; Escherichia coli O157 in spinach and beef; and Listeria monocytogenes in ready‐to‐eat meats. Public health impact is measured by disability‐adjusted life years and the cost of illness. Market impact is quantified by the economic importance of the domestic market. Likert‐type scales are used to capture consumer perception and acceptance of risk and social sensitivity to impacts on vulnerable consumer groups and industries. Risk ranking is facilitated through the development of a knowledge database presented in the format of info cards and the use of multicriteria decision analysis (MCDA) to aggregate the four factors. Three scenarios representing different stakeholders illustrate the use of MCDA to arrive at rankings of pathogen‐food combinations that reflect different criteria weights. The framework provides a flexible instrument to support policymakers in complex risk prioritization decision making when different stakeholder groups are involved and when multiple pathogen‐food combinations are compared.     

Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.     

Science and Decisions: Advancing Risk Assessment

At the request of the U.S. Environmental Protection Agency (EPA), the National Research Council (NRC) recently completed a major report, Science and Decisions: Advancing Risk Assessment, that is intended to strengthen the scientific basis, credibility, and effectiveness of risk assessment practices and subsequent risk management decisions. The report describes the challenges faced by risk assessment and the need to consider improvements in both the technical analyses of risk assessments (i.e., the development and use of scientific information to improve risk characterization) and the utility of risk assessments (i.e., making assessments more relevant and useful for risk management decisions). The report tackles a number of topics relating to improvements in the process, including the design and framing of risk assessments, uncertainty and variability characterization, selection and use of defaults, unification of cancer and noncancer dose‐response assessment, cumulative risk assessment, and the need to increase EPA's capacity to address these improvements. This article describes and summarizes the NRC report, with an eye toward its implications for risk assessment practices at EPA.     

Risk Analysis,Decision Analysis,Causal Analysis,and Economics: A Personal Perspective from More Than 40 years Experience

I entered the field of risk analysis forty years ago from a background in physics followed by doctoral training and experience in decision analysis. I came into the Society for Risk Analysis (SRA) after participating as a committee member in the 1983 National Academies report, Risk Assessment in the Federal Government: Managing the Process. The insights and recommendations from this report, and successor reports from 1996 and 2008, merit revisiting on this 40th anniversary. Risk analysis includes risk assessment, a process of summarizing applicable science to inform decisions; and risk management, a process of making informed choices, usually involving multiple stakeholders. Inherent in both is the need to deal with complexity, uncertainty, and differing perspectives and goals. The lessons I have learned include the need for a conceptual separation of risk management from risk assessment, the benefit of an iterative dialogue between these activities, and the wisdom of articulating and assessing what we know, what we want, and what we can do as we seek to understand and manage risks affecting ourselves and those we advise.     

Variability and Uncertainty Meet Risk Management and Risk Communication

In the past decade, the use of probabilistic risk analysis techniques to quantitatively address variability and uncertainty in risks increased in popularity as recommended by the 1994 National Research Council that wrote Science and Judgment in Risk Assessment. Under the 1996 Food Quality Protection Act, for example, the U.S. EPA supported the development of tools that produce distributions of risk demonstrating the variability and/or uncertainty in the results. This paradigm shift away from the use of point estimates creates new challenges for risk managers, who now struggle with decisions about how to use distributions in decision making. The challenges for risk communication, however, have only been minimally explored. This presentation uses the case studies of variability in the risks of dying on the ground from a crashing airplane and from the deployment of motor vehicle airbags to demonstrate how better characterization of variability and uncertainty in the risk assessment lead to better risk communication. Analogies to food safety and environmental risks are also discussed. This presentation demonstrates that probabilistic risk assessment has an impact on both risk management and risk communication, and highlights remaining research issues associated with using improved sensitivity and uncertainty analyses in risk assessment.     

The Role of Decision Analysis in Risk Analysis: A Retrospective

In commemorating the 40th anniversary of Risk Analysis, this article takes a retrospective look at some of the ways in which decision analysis (as a “sibling field”) has contributed to the development both of the journal, and of risk analysis as a field. I begin with some early foundational papers from the first decade of the journal's history. I then review a number of papers that have applied decision analysis to risk problems over the years, including applications of related methods such as influence diagrams, multicriteria decision analysis, and risk matrices. The article then reviews some recent trends, from roughly the last five years, and concludes with observations about the parallel evolution of risk analysis and decision analysis over the decades—especially with regard to the importance of representing multiple stakeholder perspectives, and the importance of behavioral realism in decision models. Overall, the extensive literature surveyed here supports the view that the incorporation of decision-analytic perspectives has improved the practice of risk analysis.     

Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

As part of the celebration of the 40th anniversary of the Society for Risk Analysis and Risk Analysis: An International Journal, this essay reviews the 10 most important accomplishments of risk analysis from 1980 to 2010, outlines major accomplishments in three major categories from 2011 to 2019, discusses how editors circulate authors’ accomplishments, and proposes 10 major risk-related challenges for 2020–2030. Authors conclude that the next decade will severely test the field of risk analysis.     

Foundational Challenges for Advancing the Field and Discipline of Risk Analysis

Risk analysis as a field and discipline is about concepts, principles, approaches, methods, and models for understanding, assessing, communicating, managing, and governing risk. The foundation of this field and discipline has been subject to continuous discussion since its origin some 40 years ago with the establishment of the Society for Risk Analysis and the Risk Analysis journal. This article provides a perspective on critical foundational challenges that this field and discipline faces today, for risk analysis to develop and have societal impact. Topics discussed include fundamental questions important for defining the risk field, discipline, and science; the multidisciplinary and interdisciplinary features of risk analysis; the interactions and dependencies with other sciences; terminology and fundamental principles; and current developments and trends, such as the use of artificial intelligence.     

Desired Risk: Broadening the Social Amplification of Risk Framework1

Recently Kasperson et al.⁽⁶⁾ have proposed a conceptual framework, “The Social Amplification of Risk,” as a beginning step in developing a comprehensive theory of public experience of risk. A central goal of their effort is to systematically link technical assessments of risk with the growing findings from social scientific research. A key and growing domain of public risk experience is “desired” risk, but this is virtually neglected in the framework. This paper evaluates the scope of the “Social Amplification of Risk Framework,” asking whether it is applicable to desired risks, such as risk recreation (hang gliding, mountain climbing, and so forth). The analysis is supportive of the framework's applicability to the domain of desired risk.     

Use of Advances in Technology for Maritime Risk Assessment

The maritime industry is moving toward a "goal-setting" risk-based regime. This opens the way to safety engineers to explore and exploit flexible and advanced risk modeling and decision-making approaches in the design and operation processes. In this article, following a brief review of the current status of maritime risk assessment, a design/operation selection framework and a design/operation optimization framework are outlined. A general discussion of control engineering techniques and their application to risk modeling and decision making is given. Four novel risk modeling and decision-making approaches are then outlined with illustrative examples to demonstrate their use. Such approaches may be used as alternatives to facilitate risk modeling and decision making in situations where conventional techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in general engineering and technology are suggested with respect to risk modeling and decision making.     

Elusive Critical Elements of Transformative Risk Assessment Practice and Interpretation: Is Alternatives Analysis the Next Step?

This article argues that “game‐changing” approaches to risk analysis must focus on “democratizing” risk analysis in the same way that information technologies have democratized access to, and production of, knowledge. This argument is motivated by the author's reading of Goble and Bier's analysis, “Risk Assessment Can Be a Game‐Changing Information Technology—But Too Often It Isn't” (Risk Analysis, 2013; 33: 1942–1951), in which living risk assessments are shown to be “game changing” in probabilistic risk analysis. In this author's opinion, Goble and Bier's article focuses on living risk assessment's potential for transforming risk analysis from the perspective of risk professionals—yet, the game‐changing nature of information technologies has typically achieved a much broader reach. Specifically, information technologies change who has access to, and who can produce, information. From this perspective, the author argues that risk assessment is not a game‐changing technology in the same way as the printing press or the Internet because transformative information technologies reduce the cost of production of, and access to, privileged knowledge bases. The author argues that risk analysis does not reduce these costs. The author applies Goble and Bier's metaphor to the chemical risk analysis context, and in doing so proposes key features that transformative risk analysis technology should possess. The author also discusses the challenges and opportunities facing risk analysis in this context. These key features include: clarity in information structure and problem representation, economical information dissemination, increased transparency to nonspecialists, democratized manufacture and transmission of knowledge, and democratic ownership, control, and interpretation of knowledge. The chemical safety decision‐making context illustrates the impact of changing the way information is produced and accessed in the risk context. Ultimately, the author concludes that although new chemical safety regulations do transform access to risk information, they do not transform the costs of producing this information—rather, they change the bearer of these costs. The need for further risk assessment transformation continues to motivate new practical and theoretical developments in risk analysis and management.     

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

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.     

Nano Risk Analysis: Advancing the Science for Nanomaterials Risk Management

Scientists, activists, industry, and governments have raised concerns about health and environmental risks of nanoscale materials. The Society for Risk Analysis convened experts in September 2008 in Washington, DC to deliberate on issues relating to the unique attributes of nanoscale materials that raise novel concerns about health risks. This article reports on the overall themes and findings of the workshop, uncovering the underlying issues for each of these topics that become recurring themes. The attributes of nanoscale particles and other nanomaterials that present novel issues for risk analysis are evaluated in a risk analysis framework, identifying challenges and opportunities for risk analysts and others seeking to assess and manage the risks from emerging nanoscale materials and nanotechnologies. Workshop deliberations and recommendations for advancing the risk analysis and management of nanotechnologies are presented.     

How Much Uncertainty is Too Much and How Do We Know? A Case Example of the Assessment of Ozone Monitor Network Options

Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways-the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data-values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.     

Comparative Risk and Policy Analysis in Environmental Health

There is increasing interest in the integration of quantitative risk analysis with benefit-cost and cost-effectiveness methods to evaluate environmental health policy making and perform comparative analyses. However, the combined use of these methods has revealed deficiencies in the available methods, and the lack of useful analytical frameworks currently constrains the utility of comparative risk and policy analyses. A principal issue in integrating risk and economic analysis is the lack of common performance metrics, particularly when conducting comparative analyses of regulations with disparate health endpoints (e.g., cancer and noncancer effects or risk-benefit analysis) and quantitative estimation of cumulative risk, whether from exposure to single agents with multiple health impacts or from exposure to mixtures. We propose a general quantitative framework and examine assumptions required for performing analyses of health risks and policies. We review existing and proposed risk and health-impact metrics for evaluating policies designed to protect public health from environmental exposures, and identify their strengths and weaknesses with respect to their use in a general comparative risk and policy analysis framework. Case studies are presented to demonstrate applications of this framework with risk-benefit and air pollution risk analyses. Through this analysis, we hope to generate discussions regarding the data requirements, analytical approaches, and assumptions required for general models to be used in comparative risk and policy analysis.     

Confronting Deep Uncertainties in Risk Analysis

How can risk analysts help to improve policy and decision making when the correct probabilistic relation between alternative acts and their probable consequences is unknown? This practical challenge of risk management with model uncertainty arises in problems from preparing for climate change to managing emerging diseases to operating complex and hazardous facilities safely. We review constructive methods for robust and adaptive risk analysis under deep uncertainty. These methods are not yet as familiar to many risk analysts as older statistical and model‐based methods, such as the paradigm of identifying a single “best‐fitting” model and performing sensitivity analyses for its conclusions. They provide genuine breakthroughs for improving predictions and decisions when the correct model is highly uncertain. We demonstrate their potential by summarizing a variety of practical risk management applications.     

The Value of Improved National Exposure Information for Perchloroethylene (Perc): A Case Study for Dry Cleaners

Opportunities to improve our information about risk continue to arise and lead decision makers to indirectly address the issue of the value of improved information through resource allocation decisions. Statistical decision analysis techniques provide an analytical framework for valuing information explicitly in the context of regulatory decision making. This paper provides estimates of the value of improved national estimates of perchloroethylene (perc) exposure from U.S. dry cleaners in the context of EPA's recently promulgated National Emissions Standard for Hazardous Air Pollutants (NESHAP) with emphasis on exposure information. Consistent with the NESHAP decision, we relied on EPA's technology and economic assessments. In this first cut analysis, estimates of the exposures of workers, consumers of dry cleaning services, and the general public are probabilistically characterized to reflect uncertainty about exposure and potency. We consider the net benefits of the different control options by assessing the associated changes in the total annual population risks and valuing them in monetary terms, with no constraints placed on maximum individual risks. The results suggest that the expected value of perfect information (EVPI) about potency exceeds the EVPI about exposure. Sensitivity analyses demonstrate how the choices of the valuation parameters and distributions used to characterize uncertainty in the model affect the estimates of the value of information.     

Risk Assessment and Alternatives Assessment: Comparing Two Methodologies

The selection and use of chemicals and materials with less hazardous profiles reflects a paradigm shift from reliance on risk minimization through exposure controls to hazard avoidance. This article introduces risk assessment and alternatives assessment frameworks in order to clarify a misconception that alternatives assessment is a less effective tool to guide decision making, discusses factors promoting the use of each framework, and also identifies how and when application of each framework is most effective. As part of an assessor's decision process to select one framework over the other, it is critical to recognize that each framework is intended to perform different functions. Although the two frameworks share a number of similarities (such as identifying hazards and assessing exposure), an alternatives assessment provides a more realistic framework with which to select environmentally preferable chemicals because of its primary reliance on assessing hazards and secondary reliance on exposure assessment. Relevant to other life cycle impacts, the hazard of a chemical is inherent, and although it may be possible to minimize exposure (and subsequently reduce risk), it is challenging to assess such exposures through a chemical's life cycle. Through increased use of alternatives assessments at the initial stage of material or product design, there will be less reliance on post facto risk‐based assessment techniques because the potential for harm is significantly reduced, if not avoided, negating the need for assessing risk in the first place.     

Subsea Release of Oil from a Riser: An Ecological Risk Assessment

This study illustrates a newly developed methodology, as a part of the U.S. EPA ecological risk assessment (ERA) framework, to predict exposure concentrations in a marine environment due to underwater release of oil and gas. It combines the hydrodynamics of underwater blowout, weathering algorithms, and multimedia fate and transport to measure the exposure concentration. Naphthalene and methane are used as surrogate compounds for oil and gas, respectively. Uncertainties are accounted for in multimedia input parameters in the analysis. The 95th percentile of the exposure concentration (EC_95%) is taken as the representative exposure concentration for the risk estimation. A bootstrapping method is utilized to characterize EC_95% and associated uncertainty. The toxicity data of 19 species available in the literature are used to calculate the 5th percentile of the predicted no observed effect concentration (PNEC_5%) by employing the bootstrapping method. The risk is characterized by transforming the risk quotient (RQ), which is the ratio of EC_95% to PNEC_5%, into a cumulative risk distribution. This article describes a probabilistic basis for the ERA, which is essential from risk management and decision‐making viewpoints. Two case studies of underwater oil and gas mixture release, and oil release with no gaseous mixture are used to show the systematic implementation of the methodology, elements of ERA, and the probabilistic method in assessing and characterizing the risk.