Quantitative Risk Assessment for Microbiological Food Safety

This project aims to develop probabilistic approaches to describe and then predict the variation in physiological response of populations of a selected foodborne pathogen to environmental conditions. <P>
Novel approaches will be developed to handle limited uncertain datasets in quantitative risk assessment, and in particular to develop a framework for quantitative risk assessment of verotoxin- producing E. coli O157:H7. Techniques to be used will include Bayesian Belief Networks and Monte Carlo methods.