Risk Analysis, Vol. 35, No. 2, 2015
DOI: 10.1111/risa.12387
From the Editors
CURRENT TOPICS IN RISK ANALYSIS: RISK ANALYSIS AND EBOLA
provides a sound metaphor for combining disparate pieces of evidence. WoE is also not a clearly and uniquely defined concept. Perhaps inviting experts to make WoE-based judgments may inadvertently encourage them to project their preconceptions and affect and confirmation biases into choices of weights and conclusions, without necessarily improving the accuracy or trustworthiness of the conclusions reached. Lutter et al. propose a way to do better. They suggest that the usefulness of WoE procedures can be increased by articulating and empirically testing specific causal hypotheses (ideally formulated based on a priori scientific knowledge) related to the endpoints of interest. These hypotheses may link together to jointly support valid conclusions about how exposure can cause adverse effects. If evidence can be provided that increases in exposure A cause increases in intermediate variable B, and that increases in B cause increases in the rate or frequency of adverse outcome C in a population, then the hypothesisbased WoE framework endorsed by Lutter et al. would conclude that the weight of evidence provided by these findings is that exposure A can increase the risk of harm C. Requiring explicit formulation and testing of the hypotheses that jointly imply such a conclusion – including considering alternative, competing explanations for the data supporting each link – can provide a far sounder basis for valid inferences than simply weighting and adding or averaging scores for different quality criteria or categories of evidence.
This issue introduces a new feature for Risk Analysis: occasional short, focused discussions of current topics from the news that might benefit from the perspectives and methods of risk analysis. The main purpose of these “Current Topics in Risk Analysis” pieces will be to help increase awareness of the potential practical applications of risk analysis and to encourage the risk analysis community to apply our discipline to help address current problems. In the inaugural Current Topics piece, Area Editor Charles Haas comments on unsettled questions in the assessment, management, and communication of human health risks from Ebola in developed countries. He identifies crucial questions that should be addressed to develop more effective and better-justified policies for detecting, preventing, and containing the spread of Ebola, and concludes that the current tools of microbial risk assessment are up to the challenge of providing useful answers. We encourage readers to submit papers following up on these applied research questions, and also welcome proposals for similar short, focused Current Topics essays as opportunities arise for risk analysis to play a larger role in contributing to important realworld risk management policies and decisions.
IMPROVING THE USE OF WEIGHT-OF-EVIDENCE JUDGMENTS IN RISK ANALYSIS When do various lines of evidence – such as from epidemiology, in vitro assay results, clinical and biomarker data, and animal experiments – provide a sound, objective basis for concluding that a chemical contributes causally to increasing the risk of an adverse health effects in a population? Many “Weightof-Evidence” (WoE) schemes have been proposed to answer this question. Arguably, none of them is very satisfactory. Evidence does not naturally come with weights attached, and it is not clear that weighting
COMPARING AND COMBINING THE RESULTS FROM MULTIPLE MODELS A recurring theme in many articles in recent issues of Risk Analysis has been how to combine the predictions from multiple risk models (or multiple experts) to better inform a final risk assessment than can any of the individual models (or experts) alone. Riedmann et al. study the performance of three tools used in Europe to screen
179
C 2015 Society for Risk Analysis 0272-4332/15/0100-0179$22.00/1
180 occupational chemical exposures as part of the registration, evaluation, authorization, and restriction of chemicals (REACH) program: two tier-1 (less detailed evaluation) screening tools and one tier-2 (more detailed evaluation) screening tool. They find that the more sophisticated Tier 2 tool, which is a version of the Advanced REACH Tool (ART), is not necessarily superior to the others, especially when inputs are uncertain. They recommend one of the Tier 1 tools as a more robust default choice. Differences across models for the same chemicals suggest that they are not simply reporting the same ground truth. The question of how best to use the different models is partly addressed by noting that there are trade-offs between the accuracy and robustness (i.e., insensitivity to realistic input uncertainties) of the results from different models; thus, the authors recommend using the quality of available input data to select among alternative models. This stops short of model combination, but can still be superior to selecting a single default model independent of the input data quality. WHY DON’T WE MANAGE RISKS BETTER? Hallegatte and Rentschler point out that many actions that easily pass benefit-cost tests – from washing hands to prevent the spread of illnesses to installing early warning systems to help reduce losses from natural disasters – remain unimplemented, or are implemented only poorly. Why? The authors present a taxonomy of obstacles to effective risk management by individuals, communities, organizations, and governments. They range from limited information and resources to psychological heuristics and biases that impair individual and organizational decision-making. Obstacles beyond the control of individuals acting alone include market and government failures, missing or perverse social norms and incentives in organizations and institutions, and systemic risks that can only be addressed through collective actions. Government failures, including coordination failures among overlapping jurisdictions and political economic issues such as lack of easy accountability when managing something as nebulous as risk, or the public harm done when interest groups exchange political support for favors that come at the expense of others, also help to explain why states do not do more to fill gaps in risk management to better serve the public interest, even when it is clear what actions this would require (e.g., cleaning storm drains to reduce flood risks in Mumbai).
From the Editors The authors propose that this array of obstacles can be addressed via a “risk management obstacles analysis” that might begin by identifying and correcting perverse incentives (e.g., to take excessive risks or to fail to take worthwhile ones; to misrepresent confidence about outcomes, etc.) Once incentives are correctly designed, then providing needed information, required “nudges” or other measures necessary to change behaviors, and resources to make the needed changes can help to bring about real improvements. The authors suggest that using crises to spur political actions with long-lasting consequences, conducting national risk assessments, preparing national risk matrices, establishing National Risk Boards to help coordinate across agencies, and adopting flexible, adaptive, and robust risk management plans to deal with realistic uncertainties are all potentially valuable steps for improving risk management in practice. Many of the steps required to improve societal risk management may simultaneously improve institutions and infrastructures in ways that help to alleviate poverty and achieve other development goals. Among the valuable contributions in this paper is explicit attention to the political economics of risk management. This invites future research on a variety of topics in the intersection of political economics and risk analysis, such as the degree to which the proposed steps (first align incentives correctly, then provide needed information, behavior changes, resources, and policies) are consistent with each other. For example, if information collected from individuals or organizations affects how resources are allocated, couldn’t that create incentives to distort the information provided? Impossibility theorems in political economy, group decision theory, organizational design, and collective choice theory suggest that providing incentives that will elicit the information and behaviors needed to achieve ex post Pareto-efficient outcomes may not be easy (or, perhaps, possible). On the other hand, humans have the capacity to cooperate much more than models of purely rational agents predict. Perhaps, then, the steps proposed by Hallegatte and Rentschler can be made practical with the help of moral cultures, even if they would not work for purely rational agents. We hope to see more contributions that reveal what can be accomplished in practice in different countries and cultures to improve risk management and realization of the opportunities that better risk management makes possible.
From the Editors RISKS FROM FIRES, FLOODS, AND VOLCANOES If a severe wildfire were to break out along the Colorado Front Range next summer, how large would be the risks to human habitations, where would the risk be greatest, and how large would the probable damages be? Given the answers and uncertainties available now, do we know enough to figure out where and when to pre-position fire-fighting resources or take other measures (e.g., install fire hydrants, use fire-resistant building materials, strategically apply fuel treatments to reduce fire risks) to most effectively limit the damage? Haas et al. show how to use stochastic simulations of the spread of wildfires, together with spatially resolved maps of human populations, estimates of wildfire likelihood and intensity, transmission sources, highly valued resources and assets (HVRA), and four representative extreme weather scenarios to address such questions. Rucinska similarly overlays maps of land use and flood hazard for two cities (Wroclaw city and Raciborz) in the flood plane of the Odra River in Central Europe, concluding that the greatest flood risk (from the intersection of high flood hazard and land use that puts assets at risk) occurs in the center of each city. Jongegjan and Maaskant describe the VNK2 Flood Risk in the Netherlands probabilistic risk assessment (PRA) for all major levees in the Netherlands. This PRA quantifies the possible consequences, including deaths and economic losses, for each of a set of flood scenarios, and estimates their probabilities. The failure probability for each section of the levee system is estimated for each scenario, and the probabilities of different numbers of lives lost and economic damage amounts are quantified. Simulation allows the spread of deaths and economic losses following a breach of a levee system to be displayed on a map as hours pass, and the life-saving and loss-reducing effects of mitigation measures (such as well-organized vs. disorganized evacuations) to be estimated. The authors discuss how uncertainty and sensitivity analyses can be used to identify where additional information could be most useful in reducing uncertainties about flood risks. Finally, Eiser et al. examine public trust in different agencies, and their perceptions about whether travel restrictions were necessary and the degree of risk involved, among British and Icelandic citizens in 2012, following the Icelandic volcanic ash events and flight restrictions of 2010 and 2011. In general,
181 most subjects trusted the scientific and public authorities involved and believed that they erred on the side of caution (which may actually promote greater trust, especially in the Icelandic sample), while airlines were seen as more prone to under-estimate risk. Those who had been personally inconvenienced by travel restrictions were less likely to believe that all the restrictions were necessary, suggesting that judgments about safety and the wisdom of risk management measures at least partly reflect one’s own motives and the motives attributed to others. News media were somewhat distrusted by both British and Icelandic subjects, and seen as most likely to overestimate risks.
ENVIRONMENTAL RISKS Yao et al. consider how to characterize the spatial distribution of regional risks from many, possibly interacting, point sources of water pollution, ranking both sources and vulnerable receptors in terms of their relative contributions to water pollution risk. They use fate and transport stochastic simulation (Monte Carlo) modeling for each of many risk source units (RSUs) (each RSU including the sources contributing to a drainage outlet), together with a Choquet fuzzy integral method for mapping multiple indicators of vulnerability to vulnerability scores for aquatic ecosystem, human health, and socioeconomic factors, to characterize point source water pollution risks for the Taipu River Region of the Yangtze River Delta. A novel aspect of this work is that it allows detailed characterization of the spatial heterogeneity of risk at a regional scale. On the risk perception side, Viscusi and Zeckhauser find that direct experiences with becoming ill from drinking bacteria-contaminated tap water in the United States – a rare but occasional hazard, e.g., due to failures in water treatment – greatly outweigh indirect experiences based on the accounts of others, both in affecting perceptions of risks from drinking tap water, and in motivating protective behaviors such as buying bottled water. It is not clear whether this reflects a conviction that local conditions matter most (so that one’s own experience is far more predictive that other people’s), or the availability heuristic, or a tendency to underweight the experiences of others with different interests (the “vested interest” heuristic, introduced in this paper). Understanding why direct personal experience is weighed so heavily compared to indirect experience may be important in
182 figuring out more effective risk communication campaigns, and is a promising topic for other research methods. REDUCING ACCIDENT RISKS: DUST EXPLOSIONS AND TABLE SAWS Bayesian Networks (BNs) have been applied to an increasingly wide variety of probabilistic risk assessment, risk communication and explanation, and risk management needs in articles in Risk Analysis in recent years. Yuan et al. present an application to industrial dust explosions. They map a more traditional bow-tie approach to a BN, estimate event rates from historical data, and calculate how explosion and suppression probabilities change over time. They suggest that the calculation of a most-likely explanation for an explosion – a calculation provided by many standard BN algorithms and packages – provides a useful guide for where to allocate accident prevention resources. Likewise, studying most-likely consequences can suggest ways to mitigate them. They apply the BN approach (implemented in HUGIN, one of the main BN packages) to the real-world case of a 2001 dust explosion in a wool factory in Italy, and conclude that the most likely causes included accumulation of dust particles with sizes in the explosive range and lack of employee training and awareness of explosive dust hazards. Graham and Chang examine the toll from use of table saws in the United States (28,000 emergency department visits and 2000 finger amputations per year) and ask whether automated protection systems to reduce these injuries (e.g., systems that use infrared detectors to sense human flesh in proximity to the saw blade and that stop or move the blade when this occurs) are worth their cost. For different ways of monetizing pain and suffering, they conclude that benefit-cost analysis (BCA) can justify up to $561$753 per saw to reduce health care costs, lost productivity at work, and pain and suffering. This range is much greater than estimated costs of automated protection systems, suggesting that their health and safety benefits are well worth their costs. The authors present sensitivity analyses that illustrate the robustness of this conclusion to remaining uncertainties, especially about the average economic cost per injury.
From the Editors REDUCING TERRORISM RISKS AT AIRPORTS Suppose that a terrorist attack at an airport is ultimately defeated, but not before some damage is done. For example, an attempt to hijack a plane on the ground to use in further attacks might be thwarted before the plane takes off, and yet the hijacker might kill several people before being killed or taken into custody. Shafieezadeh et al. develop a framework that allows “partial neutralization” of an adversary during an attack, leading to attacks that are neither wholly successful nor wholly unsuccessful. They show how probabilistic risk assessment (PRA) approaches that model attackers as trying to maximize expected utility can be applied to such cases of partially successful attacks, assuming that probabilities for events such as “the defenders detect the attackers successfully in security zone i” and “the probability of neutralization of the attacker in security zone i, given engagement in security zone j” can be assessed. If a model based on such event probabilities is assumed, then it can be used to rank-order different subsets of countermeasures based on their predicted effectiveness in reducing risks. The proposed approach is illustrated by analysis of a benchmark problem in which different countermeasures are evaluated for reducing risk from modeled terrorist attacks at an airport. Required probabilities are based on assumptions, literature, and expert judgments. Terrorists are assumed to consider all commercial aircraft in the U.S. as equally attractive targets, and details of how they might respond to defender actions (e.g., by attacking only less well-defended airports, or avoiding better-defended areas within an airport) are not modeled. With these simplifications, conditions are identified under which the recommended risk-reducing measures consist of installing blast-resistant cargo containers and a video surveillance system on the airport perimeter fence. The authors suggest that the PRA approach can be extended in future to include the risk attitudes of attackers and defenders, and that it can be useful today to compare the effectiveness for reducing risk of deploying different subsets of countermeasures. Tony Cox and Karen Lowrie
DOI: 10.1111/risa.12387
From the Editors
CURRENT TOPICS IN RISK ANALYSIS: RISK ANALYSIS AND EBOLA
provides a sound metaphor for combining disparate pieces of evidence. WoE is also not a clearly and uniquely defined concept. Perhaps inviting experts to make WoE-based judgments may inadvertently encourage them to project their preconceptions and affect and confirmation biases into choices of weights and conclusions, without necessarily improving the accuracy or trustworthiness of the conclusions reached. Lutter et al. propose a way to do better. They suggest that the usefulness of WoE procedures can be increased by articulating and empirically testing specific causal hypotheses (ideally formulated based on a priori scientific knowledge) related to the endpoints of interest. These hypotheses may link together to jointly support valid conclusions about how exposure can cause adverse effects. If evidence can be provided that increases in exposure A cause increases in intermediate variable B, and that increases in B cause increases in the rate or frequency of adverse outcome C in a population, then the hypothesisbased WoE framework endorsed by Lutter et al. would conclude that the weight of evidence provided by these findings is that exposure A can increase the risk of harm C. Requiring explicit formulation and testing of the hypotheses that jointly imply such a conclusion – including considering alternative, competing explanations for the data supporting each link – can provide a far sounder basis for valid inferences than simply weighting and adding or averaging scores for different quality criteria or categories of evidence.
This issue introduces a new feature for Risk Analysis: occasional short, focused discussions of current topics from the news that might benefit from the perspectives and methods of risk analysis. The main purpose of these “Current Topics in Risk Analysis” pieces will be to help increase awareness of the potential practical applications of risk analysis and to encourage the risk analysis community to apply our discipline to help address current problems. In the inaugural Current Topics piece, Area Editor Charles Haas comments on unsettled questions in the assessment, management, and communication of human health risks from Ebola in developed countries. He identifies crucial questions that should be addressed to develop more effective and better-justified policies for detecting, preventing, and containing the spread of Ebola, and concludes that the current tools of microbial risk assessment are up to the challenge of providing useful answers. We encourage readers to submit papers following up on these applied research questions, and also welcome proposals for similar short, focused Current Topics essays as opportunities arise for risk analysis to play a larger role in contributing to important realworld risk management policies and decisions.
IMPROVING THE USE OF WEIGHT-OF-EVIDENCE JUDGMENTS IN RISK ANALYSIS When do various lines of evidence – such as from epidemiology, in vitro assay results, clinical and biomarker data, and animal experiments – provide a sound, objective basis for concluding that a chemical contributes causally to increasing the risk of an adverse health effects in a population? Many “Weightof-Evidence” (WoE) schemes have been proposed to answer this question. Arguably, none of them is very satisfactory. Evidence does not naturally come with weights attached, and it is not clear that weighting
COMPARING AND COMBINING THE RESULTS FROM MULTIPLE MODELS A recurring theme in many articles in recent issues of Risk Analysis has been how to combine the predictions from multiple risk models (or multiple experts) to better inform a final risk assessment than can any of the individual models (or experts) alone. Riedmann et al. study the performance of three tools used in Europe to screen
179
C 2015 Society for Risk Analysis 0272-4332/15/0100-0179$22.00/1
180 occupational chemical exposures as part of the registration, evaluation, authorization, and restriction of chemicals (REACH) program: two tier-1 (less detailed evaluation) screening tools and one tier-2 (more detailed evaluation) screening tool. They find that the more sophisticated Tier 2 tool, which is a version of the Advanced REACH Tool (ART), is not necessarily superior to the others, especially when inputs are uncertain. They recommend one of the Tier 1 tools as a more robust default choice. Differences across models for the same chemicals suggest that they are not simply reporting the same ground truth. The question of how best to use the different models is partly addressed by noting that there are trade-offs between the accuracy and robustness (i.e., insensitivity to realistic input uncertainties) of the results from different models; thus, the authors recommend using the quality of available input data to select among alternative models. This stops short of model combination, but can still be superior to selecting a single default model independent of the input data quality. WHY DON’T WE MANAGE RISKS BETTER? Hallegatte and Rentschler point out that many actions that easily pass benefit-cost tests – from washing hands to prevent the spread of illnesses to installing early warning systems to help reduce losses from natural disasters – remain unimplemented, or are implemented only poorly. Why? The authors present a taxonomy of obstacles to effective risk management by individuals, communities, organizations, and governments. They range from limited information and resources to psychological heuristics and biases that impair individual and organizational decision-making. Obstacles beyond the control of individuals acting alone include market and government failures, missing or perverse social norms and incentives in organizations and institutions, and systemic risks that can only be addressed through collective actions. Government failures, including coordination failures among overlapping jurisdictions and political economic issues such as lack of easy accountability when managing something as nebulous as risk, or the public harm done when interest groups exchange political support for favors that come at the expense of others, also help to explain why states do not do more to fill gaps in risk management to better serve the public interest, even when it is clear what actions this would require (e.g., cleaning storm drains to reduce flood risks in Mumbai).
From the Editors The authors propose that this array of obstacles can be addressed via a “risk management obstacles analysis” that might begin by identifying and correcting perverse incentives (e.g., to take excessive risks or to fail to take worthwhile ones; to misrepresent confidence about outcomes, etc.) Once incentives are correctly designed, then providing needed information, required “nudges” or other measures necessary to change behaviors, and resources to make the needed changes can help to bring about real improvements. The authors suggest that using crises to spur political actions with long-lasting consequences, conducting national risk assessments, preparing national risk matrices, establishing National Risk Boards to help coordinate across agencies, and adopting flexible, adaptive, and robust risk management plans to deal with realistic uncertainties are all potentially valuable steps for improving risk management in practice. Many of the steps required to improve societal risk management may simultaneously improve institutions and infrastructures in ways that help to alleviate poverty and achieve other development goals. Among the valuable contributions in this paper is explicit attention to the political economics of risk management. This invites future research on a variety of topics in the intersection of political economics and risk analysis, such as the degree to which the proposed steps (first align incentives correctly, then provide needed information, behavior changes, resources, and policies) are consistent with each other. For example, if information collected from individuals or organizations affects how resources are allocated, couldn’t that create incentives to distort the information provided? Impossibility theorems in political economy, group decision theory, organizational design, and collective choice theory suggest that providing incentives that will elicit the information and behaviors needed to achieve ex post Pareto-efficient outcomes may not be easy (or, perhaps, possible). On the other hand, humans have the capacity to cooperate much more than models of purely rational agents predict. Perhaps, then, the steps proposed by Hallegatte and Rentschler can be made practical with the help of moral cultures, even if they would not work for purely rational agents. We hope to see more contributions that reveal what can be accomplished in practice in different countries and cultures to improve risk management and realization of the opportunities that better risk management makes possible.
From the Editors RISKS FROM FIRES, FLOODS, AND VOLCANOES If a severe wildfire were to break out along the Colorado Front Range next summer, how large would be the risks to human habitations, where would the risk be greatest, and how large would the probable damages be? Given the answers and uncertainties available now, do we know enough to figure out where and when to pre-position fire-fighting resources or take other measures (e.g., install fire hydrants, use fire-resistant building materials, strategically apply fuel treatments to reduce fire risks) to most effectively limit the damage? Haas et al. show how to use stochastic simulations of the spread of wildfires, together with spatially resolved maps of human populations, estimates of wildfire likelihood and intensity, transmission sources, highly valued resources and assets (HVRA), and four representative extreme weather scenarios to address such questions. Rucinska similarly overlays maps of land use and flood hazard for two cities (Wroclaw city and Raciborz) in the flood plane of the Odra River in Central Europe, concluding that the greatest flood risk (from the intersection of high flood hazard and land use that puts assets at risk) occurs in the center of each city. Jongegjan and Maaskant describe the VNK2 Flood Risk in the Netherlands probabilistic risk assessment (PRA) for all major levees in the Netherlands. This PRA quantifies the possible consequences, including deaths and economic losses, for each of a set of flood scenarios, and estimates their probabilities. The failure probability for each section of the levee system is estimated for each scenario, and the probabilities of different numbers of lives lost and economic damage amounts are quantified. Simulation allows the spread of deaths and economic losses following a breach of a levee system to be displayed on a map as hours pass, and the life-saving and loss-reducing effects of mitigation measures (such as well-organized vs. disorganized evacuations) to be estimated. The authors discuss how uncertainty and sensitivity analyses can be used to identify where additional information could be most useful in reducing uncertainties about flood risks. Finally, Eiser et al. examine public trust in different agencies, and their perceptions about whether travel restrictions were necessary and the degree of risk involved, among British and Icelandic citizens in 2012, following the Icelandic volcanic ash events and flight restrictions of 2010 and 2011. In general,
181 most subjects trusted the scientific and public authorities involved and believed that they erred on the side of caution (which may actually promote greater trust, especially in the Icelandic sample), while airlines were seen as more prone to under-estimate risk. Those who had been personally inconvenienced by travel restrictions were less likely to believe that all the restrictions were necessary, suggesting that judgments about safety and the wisdom of risk management measures at least partly reflect one’s own motives and the motives attributed to others. News media were somewhat distrusted by both British and Icelandic subjects, and seen as most likely to overestimate risks.
ENVIRONMENTAL RISKS Yao et al. consider how to characterize the spatial distribution of regional risks from many, possibly interacting, point sources of water pollution, ranking both sources and vulnerable receptors in terms of their relative contributions to water pollution risk. They use fate and transport stochastic simulation (Monte Carlo) modeling for each of many risk source units (RSUs) (each RSU including the sources contributing to a drainage outlet), together with a Choquet fuzzy integral method for mapping multiple indicators of vulnerability to vulnerability scores for aquatic ecosystem, human health, and socioeconomic factors, to characterize point source water pollution risks for the Taipu River Region of the Yangtze River Delta. A novel aspect of this work is that it allows detailed characterization of the spatial heterogeneity of risk at a regional scale. On the risk perception side, Viscusi and Zeckhauser find that direct experiences with becoming ill from drinking bacteria-contaminated tap water in the United States – a rare but occasional hazard, e.g., due to failures in water treatment – greatly outweigh indirect experiences based on the accounts of others, both in affecting perceptions of risks from drinking tap water, and in motivating protective behaviors such as buying bottled water. It is not clear whether this reflects a conviction that local conditions matter most (so that one’s own experience is far more predictive that other people’s), or the availability heuristic, or a tendency to underweight the experiences of others with different interests (the “vested interest” heuristic, introduced in this paper). Understanding why direct personal experience is weighed so heavily compared to indirect experience may be important in
182 figuring out more effective risk communication campaigns, and is a promising topic for other research methods. REDUCING ACCIDENT RISKS: DUST EXPLOSIONS AND TABLE SAWS Bayesian Networks (BNs) have been applied to an increasingly wide variety of probabilistic risk assessment, risk communication and explanation, and risk management needs in articles in Risk Analysis in recent years. Yuan et al. present an application to industrial dust explosions. They map a more traditional bow-tie approach to a BN, estimate event rates from historical data, and calculate how explosion and suppression probabilities change over time. They suggest that the calculation of a most-likely explanation for an explosion – a calculation provided by many standard BN algorithms and packages – provides a useful guide for where to allocate accident prevention resources. Likewise, studying most-likely consequences can suggest ways to mitigate them. They apply the BN approach (implemented in HUGIN, one of the main BN packages) to the real-world case of a 2001 dust explosion in a wool factory in Italy, and conclude that the most likely causes included accumulation of dust particles with sizes in the explosive range and lack of employee training and awareness of explosive dust hazards. Graham and Chang examine the toll from use of table saws in the United States (28,000 emergency department visits and 2000 finger amputations per year) and ask whether automated protection systems to reduce these injuries (e.g., systems that use infrared detectors to sense human flesh in proximity to the saw blade and that stop or move the blade when this occurs) are worth their cost. For different ways of monetizing pain and suffering, they conclude that benefit-cost analysis (BCA) can justify up to $561$753 per saw to reduce health care costs, lost productivity at work, and pain and suffering. This range is much greater than estimated costs of automated protection systems, suggesting that their health and safety benefits are well worth their costs. The authors present sensitivity analyses that illustrate the robustness of this conclusion to remaining uncertainties, especially about the average economic cost per injury.
From the Editors REDUCING TERRORISM RISKS AT AIRPORTS Suppose that a terrorist attack at an airport is ultimately defeated, but not before some damage is done. For example, an attempt to hijack a plane on the ground to use in further attacks might be thwarted before the plane takes off, and yet the hijacker might kill several people before being killed or taken into custody. Shafieezadeh et al. develop a framework that allows “partial neutralization” of an adversary during an attack, leading to attacks that are neither wholly successful nor wholly unsuccessful. They show how probabilistic risk assessment (PRA) approaches that model attackers as trying to maximize expected utility can be applied to such cases of partially successful attacks, assuming that probabilities for events such as “the defenders detect the attackers successfully in security zone i” and “the probability of neutralization of the attacker in security zone i, given engagement in security zone j” can be assessed. If a model based on such event probabilities is assumed, then it can be used to rank-order different subsets of countermeasures based on their predicted effectiveness in reducing risks. The proposed approach is illustrated by analysis of a benchmark problem in which different countermeasures are evaluated for reducing risk from modeled terrorist attacks at an airport. Required probabilities are based on assumptions, literature, and expert judgments. Terrorists are assumed to consider all commercial aircraft in the U.S. as equally attractive targets, and details of how they might respond to defender actions (e.g., by attacking only less well-defended airports, or avoiding better-defended areas within an airport) are not modeled. With these simplifications, conditions are identified under which the recommended risk-reducing measures consist of installing blast-resistant cargo containers and a video surveillance system on the airport perimeter fence. The authors suggest that the PRA approach can be extended in future to include the risk attitudes of attackers and defenders, and that it can be useful today to compare the effectiveness for reducing risk of deploying different subsets of countermeasures. Tony Cox and Karen Lowrie
