Identifying the source of food-borne disease outbreaks: An application of Bayesian variable selection.

ABSTRACT: Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic regression. Standard epidemiological analysis practice is not formally defined and the combination of currently applied methods is subject to issues such as response misclassification, missing values, multiple testing problems and small sample estimation problems resulting in biased and possibly misleading results. In this paper, we develop a formal Bayesian variable selection method to account for misclassified responses and missing covariates, which are common complications in food-borne outbreak investigations. We illustrate the im

SUBMITTER: Jacobs R 

PROVIDER: S-EPMC6448052 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature