Network Analysis of Swine Shipments in Ontario, Canada, to Support Disease Spread Modelling and Risk-Based Disease Management

September 4, 2013 — 

Understanding contact networks are important for modelling and managing the spread and control of communicable diseases in populations. This study characterizes the swine shipment network of a multi-site production system in southwestern Ontario, Canada. Data were extracted from a company's database listing swine shipments among 251 swine farms, including 20 sow, 69 nursery and 162 finishing farms, for the 2-year period of 2006 to 2007. Several network metrics were generated. The number of shipments per week between pairs of farms ranged from 1 to 6. The medians (and ranges) of out-degree were: sow 6 (1-21), nursery 8 (0-25), and finishing 0 (0-4), over the entire 2-year study period. Corresponding estimates for in-degree of nursery and finishing farms were 3 (0-9) and 3 (0-12) respectively. Outgoing and incoming infection chains (OIC and IIC), were also measured. The medians (ranges) of the monthly OIC and IIC were 0 (0-8) and 0 (0-6), respectively, with very similar measures observed for 2-week intervals. Nursery farms exhibited high measures of centrality. This indicates that they pose greater risks of disease spread in the network. Therefore, they should be given a high priority for disease prevention and control measures affecting all age groups alike. The network demonstrated scale-free and small-world topologies as observed in other livestock shipment studies. This heterogeneity in contacts among farm types and network topologies should be incorporated in simulation models to improve their validity. In conclusion, this study provided useful epidemiological information and parameters for the control and modelling of disease spread among swine farms, for the first time from Ontario, Canada.

Dorjee S, Revie CW, Poljak Z, McNab WB, Sanchez J; Network Analysis of Swine Shipments in Ontario, Canada, to Support Disease Spread Modelling and Risk-Based Disease Management; Prev Vet Med. 2013 Jul 26. pii: S0167-5877(13)00207-9. doi: 10.1016/j.prevetmed.2013.06.008. [Epub ahead of print]