YAO ZhenFei, ZHAI YuJia, WANG XiaoLong, WANG HaoNing
Center of Conservation Medicine and Ecological Safety, Northeast Forestry University, Heilongjiang, P.R. China
College of Wildlife and Protected Area, Northeast Forestry University, Heilongjiang, P.R. China
J Vet Med Sci. 2023 Dec 27;85(12):1330-1340. doi: 10.1292/jvms.23-0146. Epub 2023 Oct 27.
The outbreaks of African Swine Fever (ASF) in China are ongoing, and the inadequate management of the pig supply chain is criticized. In the past four years, a series of preventive and control measures have been supplied national wide, while the outbreaks have not been terminated. This suggests the existing animal disease management at the district level may not be appropriate to control ASF under the current situation of the ASF outbreak in China. It is urgent to further describe real distribution areas of ASF in China. In this study, we combined four regional-scale models to predict the risk distribution of ASF in mainland China and identify risk factors related to ASF outbreaks. The results showed that the four regional-scale models were more accurate in predicting the ASF outbreaks than the nationwide scale model. The four regional-scale models identified the potential risk factors associated with ASF outbreaks, such as population density, pig density, land cover, temperature, and elevation factors. Moreover, seven clusters with high potential risk of ASF outbreaks were identified. Then, based on the results, we proposed more suitable prevention and control plans for ASF, which can assist the implementation of transport management policies within and between risk clusters.
中国非洲猪瘟（ASF）疫情仍在持续，生猪供应链管理不善受到批评。在过去四年里，全国范围内采取了一系列防控措施，但疫情仍未得到遏制。这表明，在当前中国非洲猪瘟疫情形势下，现有的县级动物疾病管理措施可能不足以控制非洲猪瘟。迫切需要进一步明确中国非洲猪瘟的实际分布区域。在本研究中，我们结合了四个区域尺度模型来预测中国大陆非洲猪瘟的风险分布，并识别与非洲猪瘟疫情相关的风险因素。结果表明，这四个区域尺度模型在预测非洲猪瘟疫情方面比全国尺度模型更为准确。这四个区域尺度模型识别出了与非洲猪瘟疫情相关的潜在风险因素，如人口密度、生猪密度、土地覆盖、温度和海拔因素。此外，还识别出了七个非洲猪瘟疫情高潜在风险集群。然后，基于这些结果，我们提出了更适合的非洲猪瘟防控计划，这有助于在风险集群内部和之间实施运输管理政策。
