ArticleTransboundary and emerging diseases2026
Modeling the Spatiotemporal Spread and Control of African Swine Fever in the Republic of Korea Using a Patch-Based Stochastic Framework.
Article in Transboundary and emerging diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Modeling the Spatiotemporal Spread and Control of African Swine Fever in the Republic of Korea Using a Patch-Based Stochastic Framework.Transboundary and emerging diseases · 2026Article
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3 authors.
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Abstract
African swine fever (ASF) in the Republic of Korea is sustained mainly by transmission among wild boars. Wild boars account for approximately 98% of detected carcasses. Outbreaks occur mostly during the cold season (November-February), which coincides with the wild boar breeding period. Despite extensive control measures, including fence installation and hunting, ASF has continued to spread southward. This study aimed to estimate spatial outbreak risk and evaluate the effects of intervention by identifying high-risk areas. We developed a patch-based stochastic model that combines seasonal ASF transmission dynamics with wild boar movement. We express the wild boar movement in the model based on habitat suitability estimated from a species distribution model (SDM) that used 15 environmental variables. Using this model, we estimated outbreak probabilities for the 2023-2024 periods and classified them into four spatial risk levels: high, mid, low, and negligible. High-risk areas accounted for 62.14% of reported carcass detections in 2023 and 81.43% in 2024. When mid- and low-risk areas were included, the overall coverage exceeded 90%. The spatial distribution of high-risk areas changed between years. High-risk areas were concentrated in Chungbuk in 2023 and in Gyeongbuk in 2024. This pattern is consistent with the observed southward spread of ASF. The model also reproduced seasonal transmission dynamics. The reproduction number was approximately 1.33 during the increase phase from November to January and decreased to about 0.89 during the following decline phase. In addition, intervention analyses showed that movement restriction reduced the number of high-risk patches by up to 61.7% in 2023 and 46.4% in 2024 under high-intensity restrictions. Overall, the proposed method provides probabilistic risk assessment at a fine spatial resolution and supports quantitative evaluation of spatially targeted ASF control strategies.
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