Decision-first modeling should guide decision making for emerging risks.

An emerging risk is characterized by scant published data, rapidly changing information, and an absence of existing models that can be directly used for prediction. Analysis may be further complicated by quickly evolving decision-maker priorities and the potential need to make decisions quickly as new information comes available. To provide a forum to discuss these challenges, a virtual conference, "Decision Making for Emerging Risks," was held on June 22-23, 2021, sponsored jointly by the Decision Analysis Society of the Institute for Operations Research and the Management Sciences and the Decision Analysis and Risk specialty group in the Society for Risk Analysis. Speakers reflected on the work to support decision-makers related to the COVID-19 pandemic as well as experiences in emerging risks across domains from cybersecurity, infrastructure, transportation, energy, food safety, national security, and climate change. Here, we distill the key findings to propose a set of best practice principles for a "decision-first" approach for emerging risks. These discussions underscore the importance of scoping the decision context and the shared responsibility for the development and implementation of the analysis between the analyst and the decision-maker when the context can evolve rapidly. Emerging risks may also favor simpler analytical approaches that increase transparency, ease of explanation, and ability to conduct new analyses quickly. Continued dialogue by the decision and risk analysis communities on the use and development of models for emerging risks will enhance the credibility and usefulness of these approaches.

Medical Spending for the 2001 Anthrax Letter Attacks.

ABSTRACTIntroductionThis paper assesses the total medical costs associated with the US anthrax letter attacks of 2001. This information can be used to inform policies, which may help mitigate the potential economic impacts of similar bioterrorist attacks. METHODS: Journal publications and news reports were reviewed to establish the number of people who were exposed, were potentially exposed, received prophylactics, and became ill. Where available, cost data from the anthrax letter attacks were used. Where data were unavailable, high, low, and best cost estimates were developed from the broader literature to create a cost model and establish economic impacts. RESULTS: Medical spending totaled approximately $177 million. CONCLUSIONS: The largest expenditures stemmed from self-initiated prophylaxis (worried well): people who sought prophylactic treatment without any indication that they had been exposed to anthrax letters. This highlights an area of focus for mitigating the economic impacts of future disasters. (Disaster Med Public Health Preparedness. 2019;13:539-546).

Effect of individual protective behaviors on influenza transmission: an agent-based model.

It is well established in the epidemiological literature that individual behaviors have a significant effect on the spread of infectious diseases. Agent-based models are increasingly being recognized as the next generation of epidemiological models. In this research, we use the ability of agent-based models to incorporate behavior into simulations by examining the relative importance of vaccination and social distancing, two common measures for controlling the spread of infectious diseases, with respect to seasonal influenza. We modeled health behaviour using the result of a Health Belief Model study focused on influenza. We considered a control and a treatment group to explore the effect of education on people's health-related behaviors patterns. The control group reflects the behavioral patterns of students based on their general knowledge of influenza and its interventions while the treatment group illustrates the level of behavioral changes after individuals have been educated by a health care expert. The results of this study indicate that self-initiated behaviors are successful in controlling an outbreak in a high contact rate location such as a university. Self-initiated behaviors resulted in a population attack rate decrease of 17% and a 25% reduction in the peak number of cases. The simulation also provides significant evidence for the effect of an HBM theory-based educational program to increase the rate of applying the target interventions (vaccination by 22% percent and social distancing by 41%) and consequently to control the outbreak.

Total decontamination cost of the anthrax letter attacks.

All of the costs associated with decontamination following the 2001 anthrax letter attacks were summarized, estimated, and aggregated based on existing literature and news media reports. A comprehensive list of all affected structures was compiled. Costs were analyzed by building class and decontamination type. Sampling costs and costs of worker relocation were also included. Our analysis indicates that the total cost associated with decontamination was about $320 million.

Role of detection limits in drinking water regulation.

Some commentators on environmental science and policy have claimed that advances in analytical chemistry, reflected by an ability to detect contaminants at ever-decreasing concentrations, lead to regulations stricter than justified by available toxicological data. We evaluate this claim in the context of drinking water regulation, with respect to contaminants regulated under the Safe Drinking Water Act (SDWA). We examine the relationships between historical and present maximum contaminant levels and goals in the greater context of detection capability and evaluate the extent to which different aspects of the regulatory apparatus (i.e., analytical capability, cost-benefit analysis, analysis of competing risks, and available toxicological data) influence the regulatory process. Our findings do not support the claim that decreases in detection limit lead to more stringent regulation in the context of drinking water regulation in the United States. Further, based on our analysis of the National Primary Drinking Water Regulation and existing United States Environmental Protection Agency approaches to establishing the practical quantifiable level, we conclude that in the absence of changes to the underlying toxicological model, regulatory revision is unlikely.

A Bayesian approach to a logistic regression model with incomplete information.

We consider a set of independent Bernoulli trials with possibly different success probabilities that depend on covariate values. However, the available data consist only of aggregate numbers of successes among subsets of the trials along with all of the covariate values. We still wish to estimate the parameters of a modeled relationship between the covariates and the success probabilities, e.g., a logistic regression model. In this article, estimation of the parameters is made from a Bayesian perspective by using a Markov chain Monte Carlo algorithm based only on the available data. The proposed methodology is applied to both simulation studies and real data from a dose-response study of a toxic chemical, perchlorate.