ArticlePloS one2025
Identifying effective surveillance measures for swine pathogens using contact networks and mathematical modeling.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Infectious diseases in livestock have detrimental effects on the health of animals, the livelihood of farmers, and the meat industry. Understanding the specific pathways of disease spread and evaluating the effectiveness of surveillance measures is critical to preventing large outbreaks. Direct livestock transport, transport tours-where a single truck moves livestock between multiple farms in a single journey-and contacts that livestock have with their surrounding environment have been identified as drivers of disease dissemination. The objective of this study was to assess the role of these different pathways in the transmission of several swine pathogens and to evaluate the efficacy of surveillance strategies in identifying outbreaks. To achieve this, we built contact networks for these modes of disease transmission based on empirical data from the Swiss swine production sector. We developed a stochastic, susceptible-infectious-recovered (SIR) type, herd-based model to simulate the spread of multiple pathogens within farms and between farms along the networks. We parameterized the model for Porcine Reproductive and Respiratory Syndrome (PRRS) virus, African Swine Fever (ASF) virus, and Actinobacillus pleuropneumonia (APP): three pathogens with distinct clinical patterns, modes of transmission, and contact transmission rates. The model provides insight into the contribution of different contact types to disease dispersion. Our findings highlight that direct truck transport and local spread are the main routes of between-farm transmission. In addition, we analyzed the ability of surveillance measures to detect outbreaks from these distinct pathogens spreading along the contact networks. Farmer-based surveillance programs were the only measures that consistently identified outbreaks of APP and PRRS, and they were able to identify ASF outbreaks almost 8 weeks or more before active slaughterhouse- and network-based surveillance. Our model outcomes give evidence of the prominent transmission pathways and surveillance measures, which could help establish programs to prevent the spread of swine infectious diseases.
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