Contribution of meat inspection to animal health surveillance in Swine
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The present document has been produced and adopted by the bodies identified above as authors. In accordance with Article 36 of Regulation (EC) No 178/2002, this task has been carried out exclusively by the authors in the context of a grant agreement between the European Food Safety Authority and the authors. The present document is published complying with the transparency principle to which the European Food Safety Authority is subject. It may not be considered as an output adopted by EFSA. EFSA reserves its rights, view and position as regards the issues addressed and the conclusions reached in the present document, without prejudice to the rights of the authors.
Abstract
The objective of this work was to assist a working group (WG) of Animal Health and Welfare (AHAW) Panel in developing a generic stochastic model of the meat inspection system for swine and to investigate the probability of detection of specific diseases/conditions within that system. The work involved identification and collection of data needed for the model and implementing models to quantify the potential effectiveness of meat inspection in monitoring and surveillance of swine health and welfare. Two scenarios were considered, one with inspection tasks implemented as described by current EU legislation and one with reduced inspection without palpation and incisions, i.e. using only visual inspection. For each disease/condition a case definition was elicited from experts to describe a “typical case”, i.e. the combination of signs that would be observed in at least 60% of infected animals being fit to travel to slaughter. The parameters on detection probabilities were elicited from five experts and combined as median values. Uncertainty was captured using minimum, most likely and maximum values. Over-all detection probabilities were assessed for a list of diseases/conditions provided by the WG. Results showed that under both scenarios (current vs visual-only), the probability of detecting typical cases was high. This is likely due to the definition of the typical case, which included distinct pathological signs. However, detection probabilities will be lower in early cases, which would show more subtle signs. When considering the significance of the results, the proportion of sub-clinical (i.e. undetectable) cases should also be taken into account as well as the difficulty of detecting early cases under current meat inspection practice. Ultimately, detection of typical pathological signs is only the first step in raising an alarm, and high awareness of meat inspectors is likely to be an important factor for the overall sensitivity of meat inspection.