Discerning strain effects in microbial dose-response data.

Abstract

In order to estimate the risk or probability of adverse events in risk assessment, it is necessary to identify the important variables that contribute to the risk and provide descriptions of distributions of these variables for well-defined populations. One component of modeling dose response that can create uncertainty is the inherent genetic variability among pathogenic bacteria. For many microbial risk assessments, the "default" assumption used for dose response does not account for strain or serotype variability in pathogenicity and virulence, other than perhaps, recognizing the existence of avirulent strains. However, an examination of data sets from human clinical trials in which Salmonella spp. and Campylobacter jejuni strains were administered reveals significant strain differences. This article discusses the evidence for strain variability and concludes that more biologically based alternatives are necessary to replace the default assumptions commonly used in microbial risk assessment, specifically regarding strain variability.