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Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food-Borne Diseases

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Date
2008
Dewey
Probabilités et mathématiques appliquées
Sujet
Bayesian network; Bayesian statistics; broiler; campylobacteriosis; food-borne disease; risk assessment
Journal issue
Risk Analysis
Volume
28
Number
2
Publication date
2008
Article pages
557-571
Publisher
Wiley
DOI
http://dx.doi.org/10.1111/j.1539-6924.2008.01000.x
URI
https://basepub.dauphine.fr/handle/123456789/6291
Collections
  • CEREMADE : Publications
Metadata
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Author
Albert, Isabelle
Grenier, Emmanuel
Denis, Jean-Baptiste
Rousseau, Judith
Type
Article accepté pour publication ou publié
Abstract (EN)
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: first by constructing a stochastic core model via a Bayesian network based on expert knowledge, and second, 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 “downstream” in the food chain. Moreover, the expert knowledge is introduced more simply and consistently than with classical statistical methods. Other advantages of this approach include the clear framework of an iterative learning process, considerable flexibility enabling the use of heterogeneous data, and a justified method to explore the effects of variability and uncertainty. As an illustration, we present an estimation of the probability of contracting a campylobacteriosis as a result of broiler contamination, from the standpoint of quantitative risk assessment. Although the model thus constructed is oversimplified, it clarifies the principles 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 different experts in the food chain.

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