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African horse sickness (AHS) is a devastating equine infectious disease. On 17 March 2020, it first appeared in Thailand and threatened all the South-East Asia equine industry security. Therefore, it is imperative to carry out risk warnings of the AHS in China. The maximum entropy algorithm was used to model AHS and  Culicoides  separately by using climate and non-climate variables. The least cost path (LCP) method was used to analyze the habitat connectivity of  Culicoides  with the reclassified land cover and altitude as cost factors. The models showed the mean area under the curve as 0.918 and 0.964 for AHS and  Culicoides . The prediction result map shows that there is a high risk area in the southern part of China while the habitats of the  Culicoides  are connected to each other. Therefore, the risk of introducing AHS into China is high and control of the border area should be strengthened immediately.

Predicting the possibility of African horse sickness (AHS) introduction into China using spatial risk analysis and habitat connectivity of Culicoides