A Transport and Lairage Model for Salmonella Transmission Between Pigs Applicable to EU Member States

A Transport and Lairage Model for Salmonella Transmission Between Pigs Applicable to EU Member States

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Article ID: iaor2016925
Volume: 36
Issue: 3
Start Page Number: 482
End Page Number: 497
Publication Date: Mar 2016
Journal: Risk Analysis
Authors: , , , ,
Keywords: medicine, risk, health services, transportation: general, networks, simulation, supply & supply chains
Abstract:

A model for the transmission of Salmonella between finisher pigs during transport to the abattoir and subsequent lairage has been developed, including novel factors such as environmental contamination and the effect of stress, and is designed to be adaptable for any EU Member State (MS). The model forms part of a generic farm‐to‐consumption model for Salmonella in pigs, designed to model potentially important risk factors and assess the effectiveness of interventions. In this article, we discuss the parameterization of the model for two case study MSs. For both MSs, the model predicted an increase in the average MS‐level prevalence of Salmonella‐positive pigs during both transport and lairage, accounting for a large amount of the variation between reported on‐farm prevalence and reported lymph‐node prevalence at the slaughterhouse. Sensitivity analysis suggested that stress is the most important factor during transport, while a number of factors, including environmental contamination and the dose‐response parameters, are important during lairage. There was wide variation in the model‐predicted change in prevalence in individual batches; while the majority of batches (80–90%) had no increase, in some batches the increase in prevalence was over 70% and in some cases infection was introduced into previously uninfected batches of pigs. Thus, the model suggests that while the transport and lairage stages of the farm‐to‐consumption exposure pathway are unlikely to be responsible for a large increase in average prevalence at the MS level, they can have a large effect on prevalence at an individual‐batch level.

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