| 英文摘要 |
Since 2009, re-assortment events of high pathogenic avian influenza (HPAI) H5N1 with low pathogenic avian influenza (LPAI) viruses have been detected in China, resulting in the generation of at least 13 different subtypes, such as H5N2, H5N3, H5N6 H5N8. Epidemiological investigations on waterfowl migration showed that long-distance migratory birds can play a major role in the global spread of avian influenza viruses. The clade 2.3.4.4 of HPAI H5 virus capable of rapid, global spread in domestic poultry populations poses a major threat to both global poultry production public health. Combining satellite imaging, our previous results showed that various ecological factors may have contributed to each HPAI subtype hotspots over three consecutive years, including high poultry farm density, poultry heterogeneity index, non-registered waterfowl f density higher percentage of cropping land coverage. To enhance our understanding how wild birds, including migrating birds, contributed to the poultry farm outbreaks the spreading of HPAI, we proposed a pioneer study to integrate big data, which varied by space time. We are interested in utilizing different statistical modeling machine learning to predict the potential of poultry farm HPAI outbreaks in Taiwan at the global level. |
