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Variance in Bacillus anthracis virulence assessed through Bayesian hierarchical dose–response modelling

Abstract

Aims: To develop a predictive dose–response model for describing the survival of animals exposed to Bacillus anthracis to support risk management options. Methods and Results: Dose–response curves were generated from a large dose–mortality data set (>11 000 data points) consisting of guinea pigs exposed via the inhalation route to 76 different product preparations of B. anthracis. Because of the predictive nature of the Bayesian hierarchical approach (BHA), this method was used. The utility of this method in planning for a variety of scenarios from best case to worst case was demonstrated. Conclusions: A wide range of expected virulence was observed across products. Median estimates of virulence match well with previously published statistical estimates, but upper bound values of virulence are much greater than previous statistical estimates. Significance and Impact of the Study: This study is the first meta‐analysis in open literature to estimate the dose–response relationship for B. anthracis from a very large data set, generally a rare occurrence for highly infectious pathogens. The results are also the first to suggest the extent of variability, which is contributed by product preparation and/or dissemination methods, information needed for health‐based risk management decisions in response to a deliberate release. A set of possible benchmark values produced through this analysis can be tied to the risk tolerance of the decision‐maker or available intelligence. Further, the substantial size of the data set led to the ability to assess the appropriateness of the assumed distributional form of the prior, a common limitation in Bayesian analysis.

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