How environmental conditions impact mosquito ecology and Japanese encephalitis: an eco-epidemiological approach.
Identifieur interne : 002347 ( Ncbi/Merge ); précédent : 002346; suivant : 002348How environmental conditions impact mosquito ecology and Japanese encephalitis: an eco-epidemiological approach.
Auteurs : Huai-Yu Tian [République populaire de Chine] ; Peng Bi [Australie] ; Bernard Cazelles [France] ; Sen Zhou [République populaire de Chine] ; Shan-Qian Huang [République populaire de Chine] ; Jing Yang [République populaire de Chine] ; Yao Pei [République populaire de Chine] ; Xiao-Xu Wu [République populaire de Chine] ; Shi-Hong Fu [République populaire de Chine] ; Shi-Lu Tong [Australie] ; Huan-Yu Wang [République populaire de Chine] ; Bing Xu [États-Unis]Source :
- Environment international [ 1873-6750 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
- physiologie : Culicidae.
- épidémiologie : Chine, Encéphalite japonaise.
- Animaux, Climat, Densité de population, Facteurs de risque, Humains, Humidité, Température, Vecteurs de maladie, Écosystème.
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : China.
- epidemiology : Encephalitis, Japanese.
- physiology : Culicidae.
- transmission : Encephalitis, Japanese.
- Animals, Climate, Disease Vectors, Ecosystem, Humans, Humidity, Population Density, Risk Factors, Temperature.
Abstract
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 4month lag, respectively. The two thresholds, maximum temperature of 22-23°C for mosquito development and minimum temperature of 25-26°C for JEV transmission, play key roles in the ecology of JEV. The model predicts that, in the upper regime, a 1g/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.
DOI: 10.1016/j.envint.2015.03.002
PubMed: 25771078
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pubmed:25771078Le document en format XML
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<term>China (epidemiology)</term>
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<term>Encephalitis, Japanese (transmission)</term>
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<front><div type="abstract" xml:lang="en">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 4month lag, respectively. The two thresholds, maximum temperature of 22-23°C for mosquito development and minimum temperature of 25-26°C for JEV transmission, play key roles in the ecology of JEV. The model predicts that, in the upper regime, a 1g/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.</div>
</front>
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<ISOAbbreviation>Environ Int</ISOAbbreviation>
</Journal>
<ArticleTitle>How environmental conditions impact mosquito ecology and Japanese encephalitis: an eco-epidemiological approach.</ArticleTitle>
<Pagination><MedlinePgn>17-24</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1016/j.envint.2015.03.002</ELocationID>
<ELocationID EIdType="pii" ValidYN="Y">S0160-4120(15)00052-5</ELocationID>
<Abstract><AbstractText>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 4month lag, respectively. The two thresholds, maximum temperature of 22-23°C for mosquito development and minimum temperature of 25-26°C for JEV transmission, play key roles in the ecology of JEV. The model predicts that, in the upper regime, a 1g/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.</AbstractText>
<CopyrightInformation>Copyright © 2015. Published by Elsevier Ltd.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Tian</LastName>
<ForeName>Huai-Yu</ForeName>
<Initials>HY</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Bi</LastName>
<ForeName>Peng</ForeName>
<Initials>P</Initials>
<AffiliationInfo><Affiliation>Discipline of Public Health, University of Adelaide, Adelaide, Australia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Cazelles</LastName>
<ForeName>Bernard</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>UMMISCO, UMI 209 IRD-UPMC, 93142 Bondy, France; Eco-Evolutionary Mathematic, IBENS UMR 8197, ENS, 75230 Paris Cedex 05, France.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Zhou</LastName>
<ForeName>Sen</ForeName>
<Initials>S</Initials>
<AffiliationInfo><Affiliation>Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, Tsinghua University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Huang</LastName>
<ForeName>Shan-Qian</ForeName>
<Initials>SQ</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Yang</LastName>
<ForeName>Jing</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Pei</LastName>
<ForeName>Yao</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, Tsinghua University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wu</LastName>
<ForeName>Xiao-Xu</ForeName>
<Initials>XX</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Fu</LastName>
<ForeName>Shi-Hong</ForeName>
<Initials>SH</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory for Infectious Disease Prevention and Control (SKLID), Department of Viral Encephalitis, Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, People's Republic of China.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Tong</LastName>
<ForeName>Shi-Lu</ForeName>
<Initials>SL</Initials>
<AffiliationInfo><Affiliation>School of Public Health and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4059, Australia.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Huan-Yu</ForeName>
<Initials>HY</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory for Infectious Disease Prevention and Control (SKLID), Department of Viral Encephalitis, Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, People's Republic of China; Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou, People's Republic of China. Electronic address: rainoffall@yahoo.com.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Xu</LastName>
<ForeName>Bing</ForeName>
<Initials>B</Initials>
<AffiliationInfo><Affiliation>State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, People's Republic of China; Ministry of Education Key Laboratory for Earth System Modelling, Center for Earth System Science, Tsinghua University, Beijing, People's Republic of China; Department of Geography, University of Utah, Salt Lake City, UT 84112, USA. Electronic address: bingxu@tsinghua.edu.cn.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2015</Year>
<Month>03</Month>
<Day>11</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>Netherlands</Country>
<MedlineTA>Environ Int</MedlineTA>
<NlmUniqueID>7807270</NlmUniqueID>
<ISSNLinking>0160-4120</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D002980" MajorTopicYN="Y">Climate</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D009033" MajorTopicYN="N">Culicidae</DescriptorName>
<QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D004199" MajorTopicYN="Y">Disease Vectors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D017753" MajorTopicYN="N">Ecosystem</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D004672" MajorTopicYN="N">Encephalitis, Japanese</DescriptorName>
<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000635" MajorTopicYN="N">transmission</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006813" MajorTopicYN="N">Humidity</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011156" MajorTopicYN="N">Population Density</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013696" MajorTopicYN="N">Temperature</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">China</Keyword>
<Keyword MajorTopicYN="N">Climate</Keyword>
<Keyword MajorTopicYN="N">Environmental thresholds</Keyword>
<Keyword MajorTopicYN="N">Generalized threshold models</Keyword>
<Keyword MajorTopicYN="N">Japanese encephalitis</Keyword>
<Keyword MajorTopicYN="N">Mosquito vector</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year>
<Month>09</Month>
<Day>22</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="revised"><Year>2015</Year>
<Month>02</Month>
<Day>02</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2015</Year>
<Month>03</Month>
<Day>01</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2015</Year>
<Month>3</Month>
<Day>16</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2015</Year>
<Month>3</Month>
<Day>17</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2015</Year>
<Month>12</Month>
<Day>19</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">25771078</ArticleId>
<ArticleId IdType="pii">S0160-4120(15)00052-5</ArticleId>
<ArticleId IdType="doi">10.1016/j.envint.2015.03.002</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>Australie</li>
<li>France</li>
<li>République populaire de Chine</li>
<li>États-Unis</li>
</country>
<region><li>Utah</li>
<li>Zhejiang</li>
</region>
<settlement><li>Hangzhou</li>
<li>Pékin</li>
</settlement>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Tian, Huai Yu" sort="Tian, Huai Yu" uniqKey="Tian H" first="Huai-Yu" last="Tian">Huai-Yu Tian</name>
</noRegion>
<name sortKey="Fu, Shi Hong" sort="Fu, Shi Hong" uniqKey="Fu S" first="Shi-Hong" last="Fu">Shi-Hong Fu</name>
<name sortKey="Huang, Shan Qian" sort="Huang, Shan Qian" uniqKey="Huang S" first="Shan-Qian" last="Huang">Shan-Qian Huang</name>
<name sortKey="Pei, Yao" sort="Pei, Yao" uniqKey="Pei Y" first="Yao" last="Pei">Yao Pei</name>
<name sortKey="Wang, Huan Yu" sort="Wang, Huan Yu" uniqKey="Wang H" first="Huan-Yu" last="Wang">Huan-Yu Wang</name>
<name sortKey="Wu, Xiao Xu" sort="Wu, Xiao Xu" uniqKey="Wu X" first="Xiao-Xu" last="Wu">Xiao-Xu Wu</name>
<name sortKey="Yang, Jing" sort="Yang, Jing" uniqKey="Yang J" first="Jing" last="Yang">Jing Yang</name>
<name sortKey="Zhou, Sen" sort="Zhou, Sen" uniqKey="Zhou S" first="Sen" last="Zhou">Sen Zhou</name>
</country>
<country name="Australie"><noRegion><name sortKey="Bi, Peng" sort="Bi, Peng" uniqKey="Bi P" first="Peng" last="Bi">Peng Bi</name>
</noRegion>
<name sortKey="Tong, Shi Lu" sort="Tong, Shi Lu" uniqKey="Tong S" first="Shi-Lu" last="Tong">Shi-Lu Tong</name>
</country>
<country name="France"><noRegion><name sortKey="Cazelles, Bernard" sort="Cazelles, Bernard" uniqKey="Cazelles B" first="Bernard" last="Cazelles">Bernard Cazelles</name>
</noRegion>
</country>
<country name="États-Unis"><region name="Utah"><name sortKey="Xu, Bing" sort="Xu, Bing" uniqKey="Xu B" first="Bing" last="Xu">Bing Xu</name>
</region>
</country>
</tree>
</affiliations>
</record>
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