Publication Date

January 2001

Abstract

A risk assessment model quantifying the impmiance of the major animal-food sources was developed. For modelling purposes, we combined Bayesian inference and Monte Carlo simulation. The principle was to compare the registered number of human cases caused by different Salmonella sero- and phage types with the prevalence of these types in the different sources, weighted by the amount of food source consumed. A prior distribution was included to account for the presumed differences between serotypes and food sources with respect to causing human salmonellosis. A Poisson likelihood function was used for the probability of observing the actual number of human cases given the prevalence in the sources. Based on the posterior distribution, the number of human cases attributable to each food source was estimated. The described method may prove to be an alternative to the "traditional" stable-to-table risk assessment, which often involves making a large number of assumptions.

Book Title

Proceedings of the 4th International Symposium on the Epidemiology and Control of Salmonella and other Food Borne Pathogens in Pork

Pages

349-351

Language

en

File Format

application/pdf

DOI

https://doi.org/10.31274/safepork-180809-1132

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Jan 1st, 12:00 AM

Quantifying the Contribution of Animal-food Sources to Human Salmonellosis in Denmark in 1999

Leipzig, Germany

A risk assessment model quantifying the impmiance of the major animal-food sources was developed. For modelling purposes, we combined Bayesian inference and Monte Carlo simulation. The principle was to compare the registered number of human cases caused by different Salmonella sero- and phage types with the prevalence of these types in the different sources, weighted by the amount of food source consumed. A prior distribution was included to account for the presumed differences between serotypes and food sources with respect to causing human salmonellosis. A Poisson likelihood function was used for the probability of observing the actual number of human cases given the prevalence in the sources. Based on the posterior distribution, the number of human cases attributable to each food source was estimated. The described method may prove to be an alternative to the "traditional" stable-to-table risk assessment, which often involves making a large number of assumptions.