Geographical distribution and spatiotemporal clusters of African horse sickness outbreaks in Thailand https://doi.org/10.12982/VIS.2026.022
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Abstract
African horse sickness (AHS) is a deadly infectious vector-borne disease affecting equine species. Outbreaks of the disease can cause substantial economic loss due to its high mortality rate and the virus’s ability to extend beyond endemic areas. In March 2020, Thailand experienced the first confirmed AHS case, resulting in more than 600 horses dying and the mortality rate exceeding 90%. This study aims to determine the spatial distribution of AHS in Thailand. Initially, records on the first outbreak of AHS in 2020 were used for geoprocessing and visualized distribution. Subsequently, spatial and spatial-temporal statistical analyses were performed using QGIS and SaTScan 10.1 software. The results reveal the occurrence of AHS incidents in the central, lower northeastern, eastern, and western regions of Thailand at a total of 131 locations. The spatial analysis demonstrates significant clustering of AHS in 2020. Additionally, the Getis-Ord statistic reveals a high-density (hotspot) of AHS at the central plane, encompassing the central, lower northeastern, and eastern regions of Thailand. The space-time permutation model depicts the spatiotemporal pattern of AHS. The output identifies two significant clusters in the central part of the country, covering the central, eastern, and western regions (P-value 0.000028) and another cluster in the lower northeastern region (P-value 0.012) between February and September 2020. These findings provide crucial insights into the spatial and spatiotemporal distribution of AHS in Thailand, which is necessary for improving disease management and prevention strategies.
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