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.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Integrated Analysis: Combining Risk and Economic Assessments While Preserving the Separation of Powers

This article presents a process for an integrated policy analysis that combines risk assessment and benefit-cost analysis. This concept, which explicitly combines the two types of related analyses, seems to contradict the long-accepted risk analysis paradigm of separating risk assessment and risk management since benefit-cost analysis is generally considered to be a part of risk management. Yet that separation has become a problem because benefit-cost analysis uses risk assessment results as a starting point and considerable debate over the last several years focused on the incompatibility of the use of upper bounds or "safe" point estimates in many risk assessments with benefit-cost analysis. The problem with these risk assessments is that they ignore probabilistic information. As advanced probabilistic techniques for risk assessment emerge and economic analysts receive distributions of risks instead of point estimates, the artificial separation between risk analysts and the economic/decision analysts complicates the overall analysis. In addition, recent developments in countervailing risk theory suggest that combining the risk and benefit-cost analyses is required to fully understand the complexity of choices and tradeoffs faced by the decisionmaker. This article also argues that the separation of analysis and management is important, but that benefit-cost analysis has been wrongly classified into the risk management category and that the analytical effort associated with understanding the economic impacts of risk reduction actions need to be part of a broader risk assessment process.     

Life cycle impact assessment: a challenge for risk analysts.

Modern technology, together with an advanced economy, can provide a good or service in myriad ways, giving us choices on what to produce and how to produce it. To make those choices more intelligently, society needs to know not only the market price of each alternative, but the associated health and environmental consequences. A fair comparison requires evaluating the consequences across the whole "life cycle"--from the extraction of raw materials and processing to manufacture/construction, use, and end-of-life--of each alternative. Focusing on only one stage (e.g., manufacture) of the life cycle is often misleading. Unfortunately, analysts and researchers still have only rudimentary tools to quantify the materials and energy inputs and the resulting damage to health and the environment. Life cycle assessment (LCA) provides an overall framework for identifying and evaluating these implications. Since the 1960s, considerable progress has been made in developing methods for LCA, especially in characterizing, qualitatively and quantitatively, environmental discharges. However, few of these analyses have attempted to assess the quantitative impact on the environment and health of material inputs and environmental discharges Risk analysis and LCA are connected closely. While risk analysis has characterized and quantified the health risks of exposure to a toxicant, the policy implications have not been clear. Inferring that an occupational or public health exposure carries a nontrivial risk is only the first step in formulating a policy response. A broader framework, including LCA, is needed to see which response is likely to lower the risk without creating high risks elsewhere. Even more important, LCA has floundered at the stage of translating an inventory of environmental discharges into estimates of impact on health and the environment. Without the impact analysis, policymakers must revert to some simple rule, such as that all discharges, regardless of which chemical, which medium, and where they are discharged, are equally toxic. Thus, risk analysts should seek LCA guidance in translating a risk analysis into policy conclusions or even advice to those at risk. LCA needs the help of RA to go beyond simplistic assumptions about the implications of a discharge inventory. We demonstrate the need and rationale for LCA, present a brief history of LCA, present examples of the application of this tool, note the limitations of LCA models, and present several methods for incorporating risk assessment into LCA. However, we warn the reader not to expect too much. A comprehensive comparison of the health and environmental implications of alternatives is beyond the state of the art. LCA is currently not able to provide risk analysts with detailed information on the chemical form and location of the environmental discharges that would allow detailed estimation of the risks to individuals due to toxicants. For example, a challenge for risk analysts is to estimate health and other risks where the location and chemical speciation are not characterized precisely. Providing valuable information to decisionmakers requires advances in both LCA and risk analysis. These two disciplines should be closely linked, since each has much to contribute to the other.     

The [R]Evolving Relationship Between Risk Assessment and Risk Management

In Science and Decisions: Advancing Risk Assessment, the National Research Council recommends improvements in the U.S. Environmental Protection Agency's approach to risk assessment. The recommendations aim to increase the utility of these assessments, embedding them within a new risk‐based decision‐making framework. The framework involves first identifying the problem and possible options for addressing it, conducting related analyses, then reviewing the results and making the risk management decision. Experience with longstanding requirements for regulatory impact analysis provides insights into the implementation of this framework. First, neither the Science and Decisions framework nor the framework for regulatory impact analysis should be viewed as a static or linear process, where each step is completed before moving on to the next. Risk management options are best evaluated through an iterative and integrative procedure. The extent to which a hazard has been previously studied will strongly influence analysts’ ability to identify options prior to conducting formal analyses, and these options will be altered and refined as the analysis progresses. Second, experience with regulatory impact analysis suggests that legal and political constraints may limit the range of options assessed, contrary to both existing guidance for regulatory impact analysis and the Science and Decisions recommendations. Analysts will need to work creatively to broaden the range of options considered. Finally, the usefulness of regulatory impact analysis has been significantly hampered by the inability to quantify many health impacts of concern, suggesting that the scientific improvements offered within Science and Decisions will fill an crucial research gap.     

Risk Framework for an Organizational System With Major Components

Many large organizations accomplish their various functions through interactions across their major components. Components refers to functional entities within a large complex organization, such as business sectors, academic departments, or regional divisions. The dependency between the various components can cause risk to propagate through their overall system. This article presents a risk assessment framework that integrates risk across a diverse set of components to the overall organization functions. This project addresses three major challenges: aggregating risk, estimating component interdependencies including cycles of dependencies, and propagating risk across components. The framework aggregates risk assessments through a value function for severity that is evaluated at the expected outcome of accomplishing planned goals in terms of performance, schedule, and resources. The value function, which represents risk tolerance, scales between defined points corresponding to failure and success. Different risk assessment may be aggregated together. This article presents a novel approach to establishing relationships between the various components. This article develops and compares three network risk propagation models that characterize the overall organizational risk. The U.S. Air Force has applied this risk framework to evaluate success in hypothetical future wars. The analysts employing this risk framework have informed billions of dollars of strategic investment decisions.     

Expert Views on Biological Threat Characterization for the U.S. Government: A Delphi Study

Biological threat characterization (BTC) involves laboratory research conducted for the purpose of biological defense. BTC research is important for improving biological risk assessment and informing resource prioritization. However, there are also risks involved in BTC work, including potential for escape from the laboratory or the misuse of research results. Using a modified Delphi study to gather opinions from U.S. experts in biosecurity and biodefense, this analysis explores what principles and safeguards can maximize the benefits of BTC research and ensure that it is conducted safely and securely. Delphi participants were asked to give their opinions about the need for BTC research by the U.S. government (USG); risks of conducting this research; rules or guidelines that should be in place to ensure that the work is safe and accurate; components of an effective review and prioritization process; rules for when characterization of a pathogen can be discontinued; and recommendations about who in the USG should be responsible for BTC prioritization decisions. The findings from this research reinforce the need for BTC research at the federal level as well as a need for continued review and oversight of this research to maximize its effectiveness and reduce the risks involved. It also demonstrates the need for further discussion of what would constitute a “red line” for biothreat characterization research—research that should not be performed for safety, ethical, or practical reasons—and guidelines for when there is sufficient research in a given topic area so that the research can be considered completed.     

Workforce/Population,Economy, Infrastructure,Geography, Hierarchy,and Time (WEIGHT): Reflections on the Plural Dimensions of Disaster Resilience

The concept of resilience and its relevance to disaster risk management has increasingly gained attention in recent years. It is common for risk and resilience studies to model system recovery by analyzing a single or aggregated measure of performance, such as economic output or system functionality. However, the history of past disasters and recent risk literature suggest that a single-dimension view of relevant systems is not only insufficient, but can compromise the ability to manage risk for these systems. In this article, we explore how multiple dimensions influence the ability for complex systems to function and effectively recover after a disaster. In particular, we compile evidence from the many competing resilience perspectives to identify the most critical resilience dimensions across several academic disciplines, applications, and disaster events. The findings demonstrate the need for a conceptual framework that decomposes resilience into six primary dimensions: workforce/population, economy, infrastructure, geography, hierarchy, and time (WEIGHT). These dimensions are not typically addressed holistically in the literature; often they are either modeled independently or in piecemeal combinations. The current research is the first to provide a comprehensive discussion of each resilience dimension and discuss how these dimensions can be integrated into a cohesive framework, suggesting that no single dimension is sufficient for a holistic analysis of a disaster risk management. Through this article, we also aim to spark discussions among researchers and policymakers to develop a multicriteria decision framework for evaluating the efficacy of resilience strategies. Furthermore, the WEIGHT dimensions may also be used to motivate the generation of new approaches for data analytics of resilience-related knowledge bases.     

Risk analysis under attack: How risk science can address the legal,social, and reputational liabilities faced by risk analysts

The role of the risk analyst is critical in understanding and managing uncertainty. However, there is another type of uncertainty that is rarely discussed: The legal, social, and reputational liabilities of the risk analyst. Recent events have shown that professionals participating in risk analysis can be held personally liable. It is timely and important to ask: How can risk science guide risk analysis with consideration of those liabilities, particularly in response to emerging and unprecedented risk. This paper studies this topic by: (1) Categorizing how professionals with risk analysis responsibilities have historically been held liable, and (2) developing a framework to address uncertainty related to those potential liabilities. The result of this framework will enable individual analysts and organizations to investigate and manage the expectations of risk analysts and others as they apply risk principles and methods. This paper will be of interest to risk researchers, risk professionals, and industry professionals who seek maturity within their risk programs.     

A Discussion of Findings and Their Possible Implications from a Workshop on Bioterrorism Threat Assessment and Risk Management

In November 2001, the Monterey Institute of International Studies convened a workshop on bioterrorism threat assessment and risk management. Risk assessment practitioners from various disciplines, but without specialized knowledge of terrorism, were brought together with security and intelligence threat analysts to stimulate an exchange that could be useful to both communities. This article, prepared by a subset of the participants, comments on the workshop's findings and their implications and makes three recommendations, two short term (use of threat assessment methodologies and vulnerability analysis) and one long term (application of quantitative risk assessment and modeling), regarding the practical application of risk assessment methods to bioterrorism issues.     

Advances on a Decision Analytic Approach to Exposure-Based Chemical Prioritization

The volume and variety of manufactured chemicals is increasing, although little is known about the risks associated with the frequency and extent of human exposure to most chemicals. The EPA and the recent signing of the Lautenberg Act have both signaled the need for high-throughput methods to characterize and screen chemicals based on exposure potential, such that more comprehensive toxicity research can be informed. Prior work of Mitchell et al. using multicriteria decision analysis tools to prioritize chemicals for further research is enhanced here, resulting in a high-level chemical prioritization tool for risk-based screening. Reliable exposure information is a key gap in currently available engineering analytics to support predictive environmental and health risk assessments. An elicitation with 32 experts informed relative prioritization of risks from chemical properties and human use factors, and the values for each chemical associated with each metric were approximated with data from EPA's CP_CAT database. Three different versions of the model were evaluated using distinct weight profiles, resulting in three different ranked chemical prioritizations with only a small degree of variation across weight profiles. Future work will aim to include greater input from human factors experts and better define qualitative metrics.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Public participation in life cycle assessment and risk assessment: a shared need.

Life cycle assessment (LCA) and risk assessment are operationally different but share the common purpose of supporting decisions about reducing threats to human welfare. Both analysis methods also involve a complex mixture of science and value judgments reflecting epistemological as well as moral and esthetic values. The inability of risk assessment and LCA to be "value free" has been a source of considerable controversy in both communities. Recognition of the contingent and social nature of human interpretation of the risks and environmental impacts created by public and private decisions has led to an increased appreciation of the importance of involving interested and affected parties in risk characterization. Comparison of the value-based nature of LCA and risk assessment demonstrates the need for participation in LCA. Although the need for participation by affected parties in decision-making processes is gaining acceptance, there is little agreement as to how participation should be structured. Risk assessment and LCA have a shared need for research examining the design and analysis of participation processes appropriate to a given decision context. A proposed framework recommends participation strategies designed to enhance the effectiveness of policy-driven analyses such as risk assessment and LCA based on the level of trust that interested and affected parties have for other policy participants.     

Resilience Analytics with Application to Power Grid of a Developing Region

Infrastructure development of volatile regions is a significant investment by international government and nongovernment organizations, with attendant requirements for risk management. Global development banks may be tasked to manage these investments and provide a channel between donors and borrowers. Moreover, various stakeholders from the private sector, local and international agencies, and the military can be engaged in conception, planning, and implementation of constituent projects. Emergent and future conditions of military conflict, politics, economics, technology, environment, behaviors, institutions, and society that stress infrastructure development are prevalent, and funding mechanisms are vulnerable to fraud, waste, and abuse. This article will apply resilience analytics with scenario‐based preferences to identify the stressors that most influence a prioritization of initiatives in the electric power sector of Afghanistan. The resilience in this article is conceived in terms of the degree of disruption of priorities when stressors influence the preferences of stakeholders, and ultimately a prioritization of initiatives. The ancillary results include an understanding of which initiatives contribute most and least across strategic criteria and which criteria have the most impact for the analysis. The article concludes with recommendations for risk monitoring and risk management of the portfolio of stressors through the life cycle and horizon of grid capacity expansion.     

Improving Risk-Based Decision Making for Terrorism Applications

How can we best allocate limited defensive resources to reduce terrorism risks? Dillon et al.'s Antiterrorism Risk-Based Decision Aid (ARDA) system provides a useful point of departure for addressing this crucial question by exhibiting a real-world system that calculates risk reduction scores for different portfolios of risk-reducing countermeasures and using them to rank-order different possible risk mitigation alternatives for Navy facilities. This comment points out some potential limitations of any scoring system that does not take into account risk externalities, interdependencies among threats, uncertainties that are correlated across targets, and attacker responses to alternative allocations of defensive resources. In at least some simple situations, allocations based on risk reduction scores and comparisons can inadvertently increase risks by providing intelligent attackers with valuable information, or they can fail to reduce risks as effectively as nonscoring, optimization-based approaches. These limitations of present scoring methods present exciting technical challenges and opportunities for risk analysts to develop improved methods for protecting facilities and infrastructure against terrorist threats.     

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.     

Risk Ranking of Antimicrobial‐Resistant Hazards Found in Meat in Switzerland

Human exposure to bacteria resistant to antimicrobials and transfer of related genes is a complex issue and occurs, among other pathways, via meat consumption. In a context of limited resources, the prioritization of risk management activities is essential. Since the antimicrobial resistance (AMR) situation differs substantially between countries, prioritization should be country specific. The objective of this study was to develop a systematic and transparent framework to rank combinations of bacteria species resistant to selected antimicrobial classes found in meat, based on the risk they represent for public health in Switzerland. A risk assessment model from slaughter to consumption was developed following the Codex Alimentarius guidelines for risk analysis of foodborne AMR. Using data from the Swiss AMR monitoring program, 208 combinations of animal species/bacteria/antimicrobial classes were identified as relevant hazards. Exposure assessment and hazard characterization scores were developed and combined using multicriteria decision analysis. The effect of changing weights of scores was explored with sensitivity analysis. Attributing equal weights to each score, poultry‐associated combinations represented the highest risk. In particular, contamination with extended‐spectrum β‐lactamase/plasmidic AmpC‐producing Escherichia coli in poultry meat ranked high for both exposure and hazard characterization. Tetracycline‐ or macrolide‐resistant Enterococcus spp., as well as fluoroquinolone‐ or macrolide‐resistant Campylobacter jejuni , ranked among combinations with the highest risk. This study provides a basis for prioritizing future activities to mitigate the risk associated with foodborne AMR in Switzerland. A user‐friendly version of the model was provided to risk managers; it can easily be adjusted to the constantly evolving knowledge on AMR.     

A framework for supporting health capability-based planning: Identifying and structuring health capabilities

The COVID-19 pandemic has highlighted that health security systems must be redesigned, in a way that they are better prepared and ready to cope with multiple and diverse health threats, from predictable and well-known epidemics to unexpected and challenging pandemics. A powerful way of accomplishing this goal is to focus the planning on health capabilities. This focus may enhance the ability to respond to and recover from health threats and emergencies, while helping to identify the level of resources required to maintain and build up those capabilities that are critical in ensuring the preparedness of health security systems. However, current attempts for defining and organizing health capabilities have some important limitations. First, such attempts were not designed to consider diverse scenarios and multiple health threats. Second, they provide a limited representation of capabilities and lack a systemic perspective. Third, they struggle to identify capability and resource gaps. In this article, we thus propose a new framework for identifying and structuring health capabilities and support health capability planning. The suggested framework has three main potential benefits. First, the framework may help policymakers in planning under high levels of uncertainty, by considering multiple realistic and stressful scenarios. Second, it can provide risk analysts with a more comprehensive representation of health capabilities and their complex relationships. Third, it can support planners in identifying resource and capability gaps. We illustrate the use of the framework in practice considering an outbreak scenario caused by three different health threats (COVID-19, Ebola, and Influenza viruses).     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.     

Quantifying the Establishment Likelihood of Invasive Alien Species Introductions Through Ports with Application to Honeybees in Australia

The cost of an uncontrolled incursion of invasive alien species (IAS) arising from undetected entry through ports can be substantial, and knowledge of port‐specific risks is needed to help allocate limited surveillance resources. Quantifying the establishment likelihood of such an incursion requires quantifying the ability of a species to enter, establish, and spread. Estimation of the approach rate of IAS into ports provides a measure of likelihood of entry. Data on the approach rate of IAS are typically sparse, and the combinations of risk factors relating to country of origin and port of arrival diverse. This presents challenges to making formal statistical inference on establishment likelihood. Here we demonstrate how these challenges can be overcome with judicious use of mixed‐effects models when estimating the incursion likelihood into Australia of the European (Apis mellifera) and Asian (A. cerana) honeybees, along with the invasive parasites of biosecurity concern they host (e.g., Varroa destructor). Our results demonstrate how skewed the establishment likelihood is, with one‐tenth of the ports accounting for 80% or more of the likelihood for both species. These results have been utilized by biosecurity agencies in the allocation of resources to the surveillance of maritime ports.