Abstract
African Swine Fever (ASF) is a highly contagious viral disease of swine with exceptionally high mortality in domestic pigs. Due to the lack of effective vaccine and treatment at present, the socioeconomic impact losses caused by the virus to the swine industry across the globe is very high (Blome et al., 2020). Many studies have shown that disease modeling and forecasting can provide valuable information on the overall disease impact and can be used as guideline for decision makers to evaluate their disease surveillance and control programs (Beaunée et al., 2023; Mur et al., 2018). With the recent arrival of ASF in January 2022 in Thailand, a spatially explicit agent-based model has been constructed to support the surveillance and control strategies for ASF within the country.
In this study, we used a fine scale grid with detailed pig demographic and pig movement data in Thailand to evaluate the spatio-temporal dynamics of ASF at local and national level. Our model aimed to estimate the impact of the disease under diverse interventions such as stamping out, movement restrictions, compartmentalization, and early detection. We estimated the total number of infected farms, number of infected areas and duration of the outbreak under diverse epidemiological scenarios.
Our model estimates that reducing the average days to detection from 21 to 14 days will reduce the overall epidemic impact by 43%. Our results provide high resolution information about the regions with higher impact and the complex disease spread networks developed. These results will be used to support and improve the current ASF eradication efforts in Thailand and can be easily adapted to other transboundary animal diseases or regions under different epidemiological settings.
References
Beaunée, G., Deslandes, F., & Vergu, E. (2023). Inferring ASF transmission in domestic pigs and wild boars using a paired model iterative approach. Epidemics, 42, 100665. https://doi.org/10.1016/j.epidem.2023.100665
Blome, S., Franzke, K., & Beer, M. (2020). African swine fever - A review of current knowledge. Virus research, 287, 198099. https://doi.org/10.1016/j.virusres.2020.198099
Mur, L., Sánchez-Vizcaíno, J. M., Fernández-Carrión, E., Jurado, C., Rolesu, S., Feliziani, F., Laddomada, A., & Martínez-López, B. (2018). Understanding African Swine Fever infection dynamics in Sardinia using a spatially explicit transmission model in domestic pig farms. Transboundary and emerging diseases, 65(1), 123–134. https://doi.org/10.1111/tbed.12636