Risk analysis for the highly pathogenic avian influenza in China's mainland using meta-modeling

被引:1
作者
CAO ChunXiang1
2 Beijing Institute of Microbiology and Epidemiology
3 Graduate University of the Chinese Academy of Sciences
机构
基金
中国国家自然科学基金;
关键词
highly pathogenic avian influenza; meta-modeling; remote sensing; geographical information system; Bayesian maximum entropy; logistic regression; spatiotemporal autocorrelation;
D O I
暂无
中图分类号
S855.3 [病毒病];
学科分类号
0906 ;
摘要
A logistic model was employed to correlate the outbreak of highly pathogenic avian influenza (HPAI) with related environmental factors and the migration of birds. Based on MODIS data of the normalized difference vegetation index, environmental factors were considered in generating a probability map with the aid of logistic regression. A Bayesian maximum entropy model was employed to explore the spatial and temporal correlations of HPAI incidence. The results show that proximity to water bodies and national highways was statistically relevant to the occurrence of HPAI. Migratory birds, mainly waterfowl, were important infection sources in HPAI transmission. In addition, the HPAI outbreaks had high spatiotemporal autocorrelation. This epidemic spatial range fluctuated 45 km owing to different distribution patterns of cities and water bodies. Furthermore, two outbreaks were likely to occur with a period of 22 d. The potential risk of occurrence of HPAI in China’s mainland for the period from January 23 to February 17, 2004 was simulated based on these findings, providing a useful meta-model framework for the application of environmental factors in the prediction of HPAI risk.
引用
收藏
页码:4169 / 4179
页数:11
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