Multi-network comparison of between-farm contacts for infectious disease surveillance in swine production

Abstract

Understanding how swine farms are interconnected, directly and indirectly, is essential to characterizing infectious disease transmission. This study aimed to describe the connectivity of swine farms across 11 network types, including vehicle movements (i.e., trucks and trailers), animal movements, and distance-based farm-to-farm contacts, to identify links among production types and farms likely to be consistently characterized as super-spreaders. Truck and trailer movement networks were the most densely connected, particularly for feed transport, showing connectivity levels between 98.7% and 99.7% higher than those of pig movement and distance-based networks. These networks also exhibited the highest degree and frequency of connections between farms, while the aggregated truck network, which included all truck types, showed the greatest potential to act as a bridge connecting farms. Finisher farms were highly interconnected with other farm types across all networks. Sow farms were frequently reached by other farm types, especially through feed truck movements, representing up to 8.7% of these links. We demonstrated that in vehicle movements and proximity networks, finisher farms played a major role as super-spreaders. When comparing the top 50 farms ranked by super-spreader score in each network, vehicle-based networks showed the highest similarity, with up to 89% of top-ranked farms shared between vehicle networks. In contrast, pig movement and distance-based networks identified largely distinct sets of top-ranked farms, sharing at most 4% and 8%, respectively, with other contact networks. Overall, each network exhibited a distinct connectivity structure, resulting in different sets of high-risk farms, particularly regarding potential transmission to breeding farms. These findings support the integration of multiple transmission pathways into disease surveillance.