Unraveling the contact patterns and network structure of pig shipments in the United States and its association with porcine reproductive and respiratory syndrome virus (PRRSV) outbreaks

• Published in: Preventive veterinary medicine Vol. 138; pp. 113 - 123
• Main Authors: Lee, Kyuyoung, Polson, Dale, Lowe, Erin, Main, Rodger, Holtkamp, Derald, Martínez-López, Beatriz
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.03.2017
• Subjects: Animal Husbandry - methods; Animals; Commerce; Contact Tracing - methods; Contact Tracing - veterinary; Disease Outbreaks - veterinary; Infectious disease; PED; Porcine Reproductive and Respiratory Syndrome - epidemiology; Porcine Reproductive and Respiratory Syndrome - transmission; Porcine respiratory and reproductive syndrome virus; Pork value chain; PRRS; Regression Analysis; Risk Factors; Social network analysis; Swine; United States - epidemiology; Infectious disease; Social network analysis; Swine; Pork value chain; PRRS; PED
• ISSN: 0167-5877; 1873-1716
• DOI: 10.1016/j.prevetmed.2017.02.001

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63–0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14–5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry.