Cahiers du CEREMADE

Unité Mixte de Recherche du C.N.R.S. N°7534
 
Abstract : A novel approach to the quantitative assessment of food-borne risks is proposed. The basic idea is to use Bayesian techniques in two distinct steps: …rst by constructing a stochastic core model via a Bayesian network based on expert knowledge, and secondly using the data available to improve this knowledge. Unlike the Monte Carlo simulation approach as commonly used in quantitative assessment of food-borne risks where data sets are used independently in each module, our consistent procedure incorporates information conveyed by data throughout the chain. It allows “back calculation”in the food chain model, together with the use of data obtained “dowstream”in the food chain. Moreover the expert knowledge is introduced more simply and consistently than with classical stat- istical methods. Other advantages of this approach include the clear framework of an iterative learning process, considerable ‡exibility enabling the use of heterogeneous data, and a fully justi…ed method to explore the e¤ects of variability and uncertainty. As an illustration, we present an estimation of the probability of contracting a campy- lobacteriosis as a result of broiler contamination, from the standpoint of quantitative risk assessment. Although the model thus constructed is oversimpli…ed, it clari…es the prin- ciples and properties of the method proposed, which demonstrates its ability to deal with quite complex situations and provides a useful basis for further discussions with di¤erent experts in the food chain.
 
 
Quantitative Risk Assessment from Farm to Fork and Beyond: a global Bayesian approach concerning food-borne diseases
ALBERT Isabelle, GRENIER Emmanuel, DENIS Jean-Baptiste
ROUSSEAU Judith
2007-21
07-05-2007
 
Université de PARIS - DAUPHINE
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