Predicting Disparity between ASF-Managed Areas and Wild Boar Habitats: A Case of South Korea

SIMPLE SUMMARY: African swine fever (ASF) is a highly contagious viral disease that affects domestic pigs and wild boars worldwide. For efficient and accurate ASF management, identification of potential wild boar habitats and current ASF-managed areas is crucial. In this study, we used ensemble species distribution models to estimate the potential habitats of wild boar and ASF-managed areas. We aimed to identify areas of disparity between wild boar habitats and managed areas to identify potential risk areas for ASF transmission. Additionally, we expect that this study will ensure effective management. ABSTRACT: African swine fever (ASF) is a highly contagious viral disease affecting both domestic and wild boars. Since its first outbreak in South Korea in 2019, substantial efforts have been made to prevent ASF transmission by reducing the wild boar population and eliminating infected carcasses; however, the persistence of ASF transmission has posed challenges to these efforts. To improve ASF management strategies, the limitations of current management strategies must be identified by considering disparities between wild boar habitats and ASF-managed areas with environmental and anthropogenic characteristics of wild boars and their management strategies. Here, ensemble species distribution models were used to estimate wild boar habitats and potential ASF-managed areas, with elevation, distance to urban areas, and Normalized Difference Vegetation Index as important variables. Binary maps of wild boar habitats and potential ASF-managed areas were generated using the maxSSS as the threshold criterion. Disparity areas of ASF management were identified by overlying regions evaluated as wild boar habitats with those not classified as ASF-managed areas. Dense forests near urban regions like Chungcheongbuk-do, Gyeongsangbuk-do, and Gyeongsangnam-do were evaluated as disparity areas having high risk of ASF transmission. These findings hold significant potential for refining ASF management strategies and establishing proactive control measures.