Identifying key bird species and geographical hotspots of avian influenza A (H7N9) virus in China

被引:11
|
作者
Shi, Benyun [1 ]
Zhan, Xiao-Ming [2 ]
Zheng, Jin-Xin [3 ]
Qiu, Hongjun [1 ]
Liang, Dan [6 ,7 ]
Ye, Yan-Ming [2 ]
Yang, Guo-Jing [3 ,4 ,5 ]
Liu, Yang [6 ,7 ]
Liu, Jiming [8 ]
机构
[1] Hangzhou Dianzi Univ, Sch Cyberspace, Hangzhou 310018, Zhejiang, Peoples R China
[2] Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China
[3] Jiangsu Inst Parasit Dis, Wuxi 214064, Peoples R China
[4] Swiss Trop & Publ Hlth Inst, Dept Epidemiol & Publ Hlth, Basel, Switzerland
[5] Univ Basel, Basel, Switzerland
[6] Sun Yat Sen Univ, State Key Lab Biocontrol, Dept Ecol, Guangzhou 510275, Guangdong, Peoples R China
[7] Sun Yat Sen Univ, Sch Life Sci, Guangzhou 510275, Guangdong, Peoples R China
[8] Hong Kong Baptist Univ, Dept Comp Sci, Kowloon Tong, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Avian influenza virus; Bird migration; Geographical hotspots; Phylogenetic analysis; Cross correlation function; POPULATION HISTORY; DNA-SEQUENCES; INFERENCE; TREES; EPIDEMIOLOGY; EVOLUTION; ECOLOGY;
D O I
10.1186/s40249-018-0480-x
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Background In China since the first human infection of avian influenza A (H7N9) virus was identified in 2013, it has caused serious public health concerns due to its wide spread and high mortality rate. Evidence shows that bird migration plays an essential role in global spread of avian influenza viruses. Accordingly, in this paper, we aim to identify key bird species and geographical hotspots that are relevant to the transmission of avian influenza A (H7N9) virus in China. Methods: We first conducted phylogenetic analysis on 626 viral sequences of avian influenza A (H7N9) virus isolated in chicken, which were collected from the Global Initiative on Sharing All Influenza Data (GISAID), to reveal geographical spread and molecular evolution of the virus in China. Then, we adopted the cross correlation function (CCF) to explore the relationship between the identified influenza A (H7N9) cases and the spatiotemporal distribution of migratory birds. Here, the spatiotemporal distribution of bird species was generated based on bird observation data collected from China Bird Reports, which consists of 157272 observation records about 1145 bird species. Finally, we employed a kernel density estimator to identify geographical hotspots of bird habitat/stopover that are relevant to the influenza A (H7N9) infections. Results: Phylogenetic analysis reveals the evolutionary and geographical patterns of influenza A (H7N9) infections, where cases in the same or nearby municipality/provinces are clustered together with small evolutionary differences. Moreover, three epidemic waves in chicken along the East Asian-Australasian flyway in China are distinguished from the phylogenetic tree. The CCF analysis identifies possible migratory bird species that are relevant to the influenza A(H7N9) infections in Shanghai, Jiangsu, Zhejiang, Fujian, Jiangxi, and Guangdong in China, where the six municipality/provinces account for 91.2% of the total number of isolated H7N9 cases in chicken in GISAID. Based on the spatial distribution of identified bird species, geographical hotspots are further estimated and illustrated within these typical municipality/provinces. Conclusions: In this paper, we have identified key bird species and geographical hotspots that are relevant to the spread of influenza A (H7N9) virus. The results and findings could provide sentinel signal and evidence for active surveillance, as well as strategic control of influenza A (H7N9) transmission in China.
引用
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页数:11
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