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利用基于地理信息系统的多标准分析方法识别中国非洲猪瘟发生的适宜地区。

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

机构信息

College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang, PR China; Institute of Chinese veterinary medicine, Northeast Agricultural University, Harbin, Heilongjiang, PR China.

College of Veterinary Medicine, Northeast Agricultural University, Harbin, Heilongjiang, PR China; Institute of Chinese veterinary medicine, Northeast Agricultural University, Harbin, Heilongjiang, PR China.

出版信息

Prev Vet Med. 2022 Dec;209:105794. doi: 10.1016/j.prevetmed.2022.105794. Epub 2022 Nov 1.

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.

摘要

非洲猪瘟(ASF)是一种由非洲猪瘟病毒(ASFV)引起的家猪和野猪的出血性和致命性疾病。目前既没有有效的治疗方法,也没有疫苗,因此这种疾病给中国猪肉食品系统相关利益方的生计造成了重大经济损失和不利影响。在本研究中,使用基于地理信息系统(GIS)的多准则决策分析(MCDA)方法来确定中国适合 ASF 发生的区域。从文献综述中确定了 10 个与中国 ASF 疫情相关的空间风险因素,并通过专家基于成对比较矩阵对它们之间的相对重要性进行了评估。根据评估结果,使用层次分析法(AHP)为每个风险因素计算了数值权重。根据每个因素与 ASF 发生适宜性的假设关系收集相应的地理数据,通过适宜性关系将风险因素转换为标准化地理层,然后使用加权线性组合(WLC)方法对它们进行组合,以生成 ASF 发生适宜性地图。结果表明,我们的地图在中国预测 ASF 热点方面具有较好的准确性(AUC=0.791;95%CI[0.741-0.852])。总之,本研究为中国兽医服务部门实施非洲猪瘟监测和控制措施提供了决策支持。

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