The Dynamics of Avian Influenza: Individual-Based Model with Intervention Strategies in Traditional Trade Networks in Phitsanulok Province, Thailand

Abstract

Avian influenza virus subtype H5N1 is endemic to Southeast Asia. In Thailand, avian influenza viruses continue to cause large poultry stock losses. The spread of the disease has a serious impact on poultry production especially among rural households with backyard chickens. The movements and activities of chicken traders result in the spread of the disease through traditional trade networks. In this study, we investigate the dynamics of avian influenza in the traditional trade network in Phitsanulok Province, Thailand. We also propose an individual-based model with intervention strategies to control the spread of the disease. We found that the dynamics of the disease mainly depend on the transmission probability and the virus inactivation period. This study also illustrates the appropriate virus disinfection period and the target for intervention strategies on traditional trade network. The results suggest that good hygiene and cleanliness among household traders and trader of trader areas and ensuring that any equipment used is clean can lead to a decrease in transmission and final epidemic size. These results may be useful to epidemiologists, researchers, and relevant authorities in understanding the spread of avian influenza through traditional trade networks.

From isolation to revival: trade recovery amid global health crises

“…Furthermore, countries must address factors influencing trade recovery, as various factors determine the extent of adverse effects on trade and the duration of recovery. Emerging countries need to follow and strictly enforce the standards of the World Health Organization (WHO) [ 19 ] and deal with dynamic changes in trade and supply chain nodes during GHEs [ 20 – 24 ]. These efforts should include modeling and scenario simulation based on epidemiology and economic theory [ 25 , 26 ], risk rating of GHEs [ 27 ], and artificial intelligence modeling for potential risks [ 28 ].…”