How environmental conditions impact mosquito ecology and Japanese encephalitis: An eco-epidemiological approach

作者:Tian, HY (Tian, Huai-Yu)[ 1 ] ; Bi, P (Bi, Peng)[ 2 ] ; Cazelles, B (Cazelles, Bernard)[ 3,4 ] ; Zhou, S (Zhou, Sen)[ 5 ] ; Huang, SQ (Huang, Shan-Qian)[ 1 ] ; Yang, J (Yang, Jing)[ 1 ] ; Pei, Y (Pei, Yao)[ 5 ] ; Wu, XX (Wu, Xiao-Xu)[ 1 ] ; Fu, SH (Fu, Shi-Hong)[ 6,7 ] ; Tong, SL (Tong, Shi-Lu)[ 8,9 ] ; Wang, HY (Wang, Huan-Yu)[ 6,7 ] ; Xu, B (Xu, Bing)[ 1,5,10 ] 

ENVIRONMENT INTERNATIONAL

卷: 79  页: 17-24

DOI: 10.1016/j.envint.2015.03.002

出版年: JUN 2015

摘要

Japanese encephalitis (JE) is one of the major vector-borne diseases in Southeast Asia and the Western Pacific region, posing a threat to human health. In rural and suburban areas, traditional rice farming and intensive pig breeding provide an ideal environment for both mosquito development and the transmission of JEV among human beings. Combining surveillance data for mosquito vectors, human JE cases, and environmental conditions in Changsha, China, 2004-2009, generalized threshold models were constructed to project the mosquito and JE dynamics. Temperature and rainfall were found to be closely associated with mosquito density at 1, and 4 month lag, respectively. The two thresholds, maximum temperature of 22-23 degrees C for mosquito development and minimum temperature of 25-26 degrees C for JEV transmission, play key roles in the ecology of JEV. The model predicts that, in the upper regime, a 1 g/m(3) increase in absolute humidity would on average increase human cases by 68-84%. A shift in mosquito species composition in 2007 was observed, and possibly caused by a drought. Effective predictive models could be used in risk management to provide early warnings for potential JE transmission. (C) 2015 Published by Elsevier Ltd.

通讯作者地址: Wang, HY (通讯作者)

Chinese Ctr Dis Control & Prevent, Inst Viral Dis Control & Prevent, Dept Viral Encephalitis, State Key Lab Infect Dis Prevent & Control SKLID, Beijing 102206, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Coll Global Change & Earth Syst Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China

[ 2 ] Univ Adelaide, Discipline Publ Hlth, Adelaide, SA, Australia

[ 3 ] UPMC, UMI IRD 209, UMMISCO, Bondy, France

[ 4 ] ENS, IBENS UMR 8197, Ecoevolutionary Math, F-75230 Paris 05, France

[ 5 ] Tsinghua Univ, Ctr Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modelling, Beijing 100084, Peoples R China

[ 6 ] Chinese Ctr Dis Control & Prevent, Inst Viral Dis Control & Prevent, Dept Viral Encephalitis, State Key Lab Infect Dis Prevent & Control SKLID, Beijing 102206, Peoples R China

[ 7 ] Collaborat Innovat Ctr Diag & Treatment Infect Di, Hangzhou, Zhejiang, Peoples R China

[ 8 ] Queensland Univ Technol, Sch Publ Hlth, Brisbane, Qld 4059, Australia

[ 9 ] Queensland Univ Technol, Inst Hlth & Biomed Innovat, Brisbane, Qld 4059, Australia

[ 10 ] Univ Utah, Dept Geog, Salt Lake City, UT 84112 USA