Simulation modeling of influenza transmission through backyard pig trade networks in a wildlife/livestock interface area.

Influenza constitutes a challenge to animal and human health. It is a highly contagious disease with wildlife reservoirs and considered as endemic among swine populations. Pigs are crucial in the disease dynamics due to their capacity to generate new reassortant viruses. The risk of informal animal trade in the spread of zoonotic diseases is well recognized worldwide. Nevertheless, the contribution of the backyard pig trade network in the transmission of influenza in a wildlife/livestock interface area is unknown. This study provides the first simulation of influenza transmission based on backyard farm connections in Mexico. A susceptible-infectious-recovered (SIR) model was implemented using the Epimodel software package in R, and 260 backyard farms were considered as nodes. Three different scenarios of connectivity (low, medium, and high) mediated by trade were generated and compared. Our results suggest that half of the pig population were infected within 5 days in the high connectivity scenario and the number of infected farms was approximately 65-fold higher compared to the low connected one. The consequence of connectivity variations directly influenced both time and duration of influenza virus transmission. Therefore, high connectivity driven by informal trade constitutes a significant risk to animal health. Trade patterns of animal movements are complex. This approach emphasizes the importance of pig movements and spatial dynamics among backyard production, live animal markets, and wildlife.