Environmental factors and spatiotemporal distribution characteristics of the global outbreaks of the highly pathogenic avian influenza H5N1

被引:14
作者
Chen, Wei [1 ]
Zhang, Xuepeng [1 ]
Zhao, Wenwu [2 ,3 ]
Yang, Lan [1 ]
Wang, Zhe [1 ]
Bi, Hongru [1 ]
机构
[1] China Univ Min & Technol, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China
[2] Beijing Normal Univ, Fac Geog Sci, Inst Land Surface Syst & Sustainable Dev, Beijing 100875, Peoples R China
[3] Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
基金
国家重点研发计划;
关键词
Remote sensing; Spatiotemporal analysis; Binary logistic regression; COVID-19; Responsible Editor; Lotfi Aleya; RISK-FACTORS; VIRUS; CHINA; POULTRY; MODEL;
D O I
10.1007/s11356-022-19016-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The spread of highly pathogenic avian influenza H5N1 has posed a major threat to global public health. Understanding the spatiotemporal outbreak characteristics and environmental factors of H5N1 outbreaks is of great significance for the establishment of effective prevention and control systems. The time and location of H5N1 outbreaks in poultry and wild birds officially confirmed by the World Organization for Animal Health from 2005 to 2019 were collected. Spatial autocorrelation analysis and multidistance spatial agglomeration analysis methods were used to analyze the global outbreak sites of H5N1. Combined with remote sensing data, the correlation between H5N1 outbreaks and environmental factors was analyzed using binary logistic regression methods. We analyzed the correlation between the H5N1 outbreak and environmental factors and finally made a risk prediction for the global H5N1 outbreaks. The results show that the peak of the H5N1 outbreaks occurs in winter and spring. H5N1 outbreaks exhibit aggregation, and a weak aggregation phenomenon is noted on the scale close to 5000 km. Water distance, road distance, railway distance, wind speed, leaf area index (LAI), and specific humidity were protective factors for the outbreak of H5N1, and the odds ratio (OR) were 0.985, 0.989, 0.995, 0.717, 0.832, and 0.935, respectively. Temperature was a risk factor with an OR of 1.073. The significance of these ORs was greater than 95%. The global risk prediction map was obtained. Given that the novel coronavirus (COVID-19) is spreading globally, the methods and results of this study can provide a reference for studying the spread of COVID-19.
引用
收藏
页码:44175 / 44185
页数:11
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