Identification of suitable areas for African swine fever occurrence in china using geographic information system-based multi-criteria analysis

Abstract

African swine fever (ASF) is a hemorrhagic and fatal disease of domestic pigs and wild boars caused by the African swine fever virus (ASFV). There is neither effective treatment nor vaccine at present, and thus this disease has led to major economic losses and adverse impacts on the livelihoods of stakeholders involved in the pork food system in China. In this study, a multi-criteria decision analysis (MCDA) method based on a geographic information system (GIS) was used to identify suitable areas for ASF occurrence in China. Ten spatial risk factors regarding ASF epidemic in China were identified from literature reviews, and the relative importance between them was evaluated by experts based on a pairwise comparison matrix. A numerical weight was calculated for each risk factor using an analytic hierarchy process (AHP) based on the evaluated results. The corresponding geographic data were collected, according to the hypothetical relationship between each factor and the suitability for ASF occurrence, risk factors were converted to standardized geographical layers using suitability relationship and then were combined using a weighted linear combination (WLC) method to produce a map of suitability for ASF occurrence. The results showed that our map has good accuracy in predicting the hot- spots of ASF in China (AUC =0.791; 95% CI [0.741–0.852]). In conclusion, our study provides decision-making aid support for Chinese veterinary services to implement African swine fever surveillance and control measures.