Distribution and Risk Factors of 2009 Pandemic Influenza A (H1N1) in Mainland China
Identifieur interne : 002211 ( Main/Merge ); précédent : 002210; suivant : 002212Distribution and Risk Factors of 2009 Pandemic Influenza A (H1N1) in Mainland China
Auteurs : Li-Qun Fang [République populaire de Chine, Pays-Bas] ; Li-Ping Wang [République populaire de Chine] ; Sake J. De Vias [Pays-Bas] ; SONG LIANG [États-Unis] ; Shi-Lu Tong [Australie] ; Yan-Li Li [République populaire de Chine] ; Ya-Pin Li [République populaire de Chine] ; QUAN QIAN [République populaire de Chine] ; HONG YANG [République populaire de Chine] ; Mai-Geng Zhou [République populaire de Chine] ; Xiao-Feng Wang [République populaire de Chine] ; Jan Hendrik Richardus [Pays-Bas] ; Jia-Qi Ma [République populaire de Chine] ; Wu-Chun Cao [République populaire de Chine]Source :
- American journal of epidemiology [ 0002-9262 ] ; 2012.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Santé publique, Maladie, Homme.
English descriptors
- KwdEn :
Abstract
Data from all reported cases of 2009 pandemic influenza A (H1N1) were obtained from the China Information System for Disease Control and Prevention. The spatiotemporal distribution patterns of cases were characterized through spatial analysis. The impact of travel-related risk factors on invasion of the disease was analyzed using survival analysis, and climatic factors related to local transmission were identified using multilevel Poisson regression, both at the county level. The results showed that the epidemic spanned a large geographic area, with the most affected areas being in western China. Significant differences in incidence were found among age groups, with incidences peaking in school-age children. Overall, the epidemic spread from southeast to northwest. Proximity to airports and being intersected by national highways or freeways but not railways were variables associated with the presence of the disease in a county. Lower temperature and lower relative humidity were the climatic factors facilitating local transmission after correction for the effects of school summer vacation and public holidays, as well as population density and the density of medical facilities. These findings indicate that interventions focused on domestic travel, population density, and climatic factors could play a role in mitigating the public health impact of future influenza pandemics.
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Pascal:12-0221312Le document en format XML
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Distribution and Risk Factors of 2009 Pandemic Influenza A (H1N1) in Mainland China</title>
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<author><name sortKey="Song Liang" sort="Song Liang" uniqKey="Song Liang" last="Song Liang">SONG LIANG</name>
<affiliation wicri:level="2"><inist:fA14 i1="04"><s1>Department of Environmental Health Sciences, College of Public Health, Ohio State University</s1>
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<author><name sortKey="Tong, Shi Lu" sort="Tong, Shi Lu" uniqKey="Tong S" first="Shi-Lu" last="Tong">Shi-Lu Tong</name>
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<author><name sortKey="Li, Yan Li" sort="Li, Yan Li" uniqKey="Li Y" first="Yan-Li" last="Li">Yan-Li Li</name>
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<author><name sortKey="Hong Yang" sort="Hong Yang" uniqKey="Hong Yang" last="Hong Yang">HONG YANG</name>
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<author><name sortKey="Wang, Xiao Feng" sort="Wang, Xiao Feng" uniqKey="Wang X" first="Xiao-Feng" last="Wang">Xiao-Feng Wang</name>
<affiliation wicri:level="3"><inist:fA14 i1="03"><s1>National Center for Public Health Surveillance and Information Service, Chinese Center for Disease Control and Prevention</s1>
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<affiliation wicri:level="3"><inist:fA14 i1="02"><s1>Department of Public Health, Erasmus Medical Center, University Medical Center Rotterdam</s1>
<s2>Rotterdam</s2>
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</placeName>
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<author><name sortKey="Ma, Jia Qi" sort="Ma, Jia Qi" uniqKey="Ma J" first="Jia-Qi" last="Ma">Jia-Qi Ma</name>
<affiliation wicri:level="3"><inist:fA14 i1="03"><s1>National Center for Public Health Surveillance and Information Service, Chinese Center for Disease Control and Prevention</s1>
<s2>Beijing</s2>
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<author><name sortKey="Cao, Wu Chun" sort="Cao, Wu Chun" uniqKey="Cao W" first="Wu-Chun" last="Cao">Wu-Chun Cao</name>
<affiliation wicri:level="3"><inist:fA14 i1="01"><s1>State Key Laboratory of Pathogens and Biosecurity, Beijing Institute of Microbiology and Epidemiology</s1>
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</author>
</analytic>
<series><title level="j" type="main">American journal of epidemiology</title>
<title level="j" type="abbreviated">Am. j. epidemiol.</title>
<idno type="ISSN">0002-9262</idno>
<imprint><date when="2012">2012</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">American journal of epidemiology</title>
<title level="j" type="abbreviated">Am. j. epidemiol.</title>
<idno type="ISSN">0002-9262</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>2009</term>
<term>China</term>
<term>Disease</term>
<term>Distribution</term>
<term>Epidemic</term>
<term>Epidemiology</term>
<term>H1N1 influenza</term>
<term>Human</term>
<term>Infection</term>
<term>Influenza A (H1N1)</term>
<term>Invasion</term>
<term>Metastasis</term>
<term>Public health</term>
<term>Risk factor</term>
<term>Transmission</term>
<term>Tumorous infiltration</term>
<term>World</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Infection</term>
<term>Métastase</term>
<term>Distribution</term>
<term>Facteur risque</term>
<term>2009</term>
<term>Santé publique</term>
<term>Chine</term>
<term>Maladie</term>
<term>Epidémie</term>
<term>Transmission</term>
<term>Homme</term>
<term>Infiltration tumorale</term>
<term>Invasion</term>
<term>Monde</term>
<term>Epidémiologie</term>
<term>Pandémie</term>
<term>Grippe H1N1</term>
<term>Virus grippal A(H1N1)</term>
</keywords>
<keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Santé publique</term>
<term>Maladie</term>
<term>Homme</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Data from all reported cases of 2009 pandemic influenza A (H1N1) were obtained from the China Information System for Disease Control and Prevention. The spatiotemporal distribution patterns of cases were characterized through spatial analysis. The impact of travel-related risk factors on invasion of the disease was analyzed using survival analysis, and climatic factors related to local transmission were identified using multilevel Poisson regression, both at the county level. The results showed that the epidemic spanned a large geographic area, with the most affected areas being in western China. Significant differences in incidence were found among age groups, with incidences peaking in school-age children. Overall, the epidemic spread from southeast to northwest. Proximity to airports and being intersected by national highways or freeways but not railways were variables associated with the presence of the disease in a county. Lower temperature and lower relative humidity were the climatic factors facilitating local transmission after correction for the effects of school summer vacation and public holidays, as well as population density and the density of medical facilities. These findings indicate that interventions focused on domestic travel, population density, and climatic factors could play a role in mitigating the public health impact of future influenza pandemics.</div>
</front>
</TEI>
<affiliations><list><country><li>Australie</li>
<li>Pays-Bas</li>
<li>République populaire de Chine</li>
<li>États-Unis</li>
</country>
<region><li>Hollande-Méridionale</li>
<li>Ohio</li>
</region>
<settlement><li>Pékin</li>
<li>Rotterdam</li>
</settlement>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Fang, Li Qun" sort="Fang, Li Qun" uniqKey="Fang L" first="Li-Qun" last="Fang">Li-Qun Fang</name>
</noRegion>
<name sortKey="Cao, Wu Chun" sort="Cao, Wu Chun" uniqKey="Cao W" first="Wu-Chun" last="Cao">Wu-Chun Cao</name>
<name sortKey="Hong Yang" sort="Hong Yang" uniqKey="Hong Yang" last="Hong Yang">HONG YANG</name>
<name sortKey="Li, Ya Pin" sort="Li, Ya Pin" uniqKey="Li Y" first="Ya-Pin" last="Li">Ya-Pin Li</name>
<name sortKey="Li, Yan Li" sort="Li, Yan Li" uniqKey="Li Y" first="Yan-Li" last="Li">Yan-Li Li</name>
<name sortKey="Ma, Jia Qi" sort="Ma, Jia Qi" uniqKey="Ma J" first="Jia-Qi" last="Ma">Jia-Qi Ma</name>
<name sortKey="Quan Qian" sort="Quan Qian" uniqKey="Quan Qian" last="Quan Qian">QUAN QIAN</name>
<name sortKey="Wang, Li Ping" sort="Wang, Li Ping" uniqKey="Wang L" first="Li-Ping" last="Wang">Li-Ping Wang</name>
<name sortKey="Wang, Xiao Feng" sort="Wang, Xiao Feng" uniqKey="Wang X" first="Xiao-Feng" last="Wang">Xiao-Feng Wang</name>
<name sortKey="Zhou, Mai Geng" sort="Zhou, Mai Geng" uniqKey="Zhou M" first="Mai-Geng" last="Zhou">Mai-Geng Zhou</name>
</country>
<country name="Pays-Bas"><region name="Hollande-Méridionale"><name sortKey="Fang, Li Qun" sort="Fang, Li Qun" uniqKey="Fang L" first="Li-Qun" last="Fang">Li-Qun Fang</name>
</region>
<name sortKey="De Vias, Sake J" sort="De Vias, Sake J" uniqKey="De Vias S" first="Sake J." last="De Vias">Sake J. De Vias</name>
<name sortKey="Richardus, Jan Hendrik" sort="Richardus, Jan Hendrik" uniqKey="Richardus J" first="Jan Hendrik" last="Richardus">Jan Hendrik Richardus</name>
</country>
<country name="États-Unis"><region name="Ohio"><name sortKey="Song Liang" sort="Song Liang" uniqKey="Song Liang" last="Song Liang">SONG LIANG</name>
</region>
</country>
<country name="Australie"><noRegion><name sortKey="Tong, Shi Lu" sort="Tong, Shi Lu" uniqKey="Tong S" first="Shi-Lu" last="Tong">Shi-Lu Tong</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
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