Risk analysis for the highly pathogenic avian influenza in Mainland China using meta-modeling

被引:38
作者
Cao ChunXiang [1 ]
Xu Min [1 ,3 ]
Chang ChaoYi [1 ,3 ]
Xue Yong [1 ]
Zhong ShaoBo [1 ]
Fang LiQun [2 ]
Cao WuChun [2 ]
Zhang Hao [1 ]
Gao MengXu [1 ,3 ]
He QiSheng [1 ,3 ]
Zhao Jian [1 ,3 ]
Chen Wei [1 ,3 ]
Zheng Sheng [1 ,3 ]
Li XiaoWen [1 ]
机构
[1] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China
[2] Beijing Inst Microbiol & Epidemiol, State Key Lab Pathogen & Biosecur, Beijing 100071, Peoples R China
[3] Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
来源
CHINESE SCIENCE BULLETIN | 2010年 / 55卷 / 36期
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; H5N1; VIRUS;
D O I
10.1007/s11434-010-4225-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
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 Mainland China 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:4168 / 4178
页数:11
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