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Estimating the velocity and direction of African Swine Fever spread in wild boar populations in South Korea using Trend-Surface Analysis

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2026

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Public Library of Science
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Aguilar-Vega, C., Bosch, J., Ito, S., Ivorra, B., Jeong, H., & Sánchez-Vizcaíno, J. M. (2026). Estimating the velocity and direction of African Swine Fever spread in wild boar populations in South Korea using Trend-Surface Analysis. PloS one, 21(4), e0346098. https://doi.org/10.1371/journal.pone.0346098

Abstract

African swine fever (ASF) is a lethal disease of swine that has spread across Asia since its introduction in 2018. South Korea first reported the disease in September 2019 in domestic pigs, and since then, more than 4,000 cases have been reported in wild boars during its expansion up to August 2024. Due to the high number of ASF notifications in wild boars in South Korea, contrasted with their scarcity in most Asian countries, analyzing the spatiotemporal spread of the disease in a setting with active surveillance provides valuable insights. In this study, we performed a trend-surface analysis on temporally gridded case data to characterize the overall geographic spread and direction of ASF in wild boars across South Korea, from its emergence to August 2022. Additionally, we propose a novel approach distinct from previous studies, to estimate spread velocity by incorporating an upper threshold to avoid unrealistic values. The model described the spread of ASF in the study area. The disease showed greater expansion in the east of the country. Initially, a south and eastward direction was estimated. The estimated median velocity was 19.53 km/month, with cell-level velocities ranging from 2.45 to 69.99 km/month. Velocity increased notably from autumn 2021 onward and varied substantially across years. Our results show the dynamics of ASF in wild boars of South Korea, providing new evidence of their role in the epidemiology of the disease.

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Author contributions Conceptualization: Cecilia Aguilar-Vega, Jaime Bosch, Satoshi Ito, José Manuel Sánchez-Vizcaíno. Data curation: Cecilia Aguilar-Vega, Satoshi Ito. PLOS One | https://doi.org/10.1371/journal.pone.0346098 April 2, 2026 11 / 13 Formal analysis: Cecilia Aguilar-Vega. Funding acquisition: Benjamin Ivorra, José Manuel Sánchez-Vizcaíno. Investigation: Satoshi Ito, Hyunkyu Jeong. Methodology: Cecilia Aguilar-Vega, Jaime Bosch, Benjamin Ivorra. Project administration: Jaime Bosch, Benjamin Ivorra, José Manuel Sánchez-Vizcaíno. Resources: Satoshi Ito, Hyunkyu Jeong. Software: Cecilia Aguilar-Vega. Supervision: Jaime Bosch, José Manuel Sánchez-Vizcaíno. Validation: Cecilia Aguilar-Vega, Jaime Bosch, Satoshi Ito, Benjamin Ivorra. Visualization: Cecilia Aguilar-Vega. Writing – original draft: Cecilia Aguilar-Vega. Writing – review & editing: Cecilia Aguilar-Vega, Jaime Bosch, Satoshi Ito, Benjamin Ivorra, Hyunkyu Jeong, José Manuel Sánchez-Vizcaíno.

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