Roles of Different Transport Modes in the Spatial Spread of the 2009 Influenza A(H1N1) Pandemic in Mainland China
Identifieur interne : 001F15 ( Ncbi/Checkpoint ); précédent : 001F14; suivant : 001F16Roles of Different Transport Modes in the Spatial Spread of the 2009 Influenza A(H1N1) Pandemic in Mainland China
Auteurs : Jun Cai [République populaire de Chine] ; Bo Xu [République populaire de Chine] ; Karen Kie Yan Chan [République populaire de Chine] ; Xueying Zhang ; Bing Zhang ; Ziyue Chen ; Bing Xu [République populaire de Chine]Source :
- International Journal of Environmental Research and Public Health [ 1661-7827 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
- épidémiologie : Chine, Grippe humaine.
- Humains, Réseaux de transports, Sous-type H1N1 du virus de la grippe A, Transports, Voyage.
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic , epidemiology : China.
- epidemiology : Influenza, Human.
- transmission : Influenza, Human.
- Humans, Influenza A Virus, H1N1 Subtype, Transportation, Transportation Facilities, Travel.
Abstract
There is increasing concern about another influenza pandemic in China. However, the understanding of the roles of transport modes in the 2009 influenza A(H1N1) pandemic spread across mainland China is limited. Herein, we collected 127,797 laboratory-confirmed cases of influenza A(H1N1)pdm09 in mainland China from May 2009 to April 2010. Arrival days and peak days were calculated for all 340 prefectures to characterize the dissemination patterns of the pandemic. We first evaluated the effects of airports and railway stations on arrival days and peak days, and then we applied quantile regressions to quantify the relationships between arrival days and air, rail, and road travel. Our results showed that early arrival of the virus was not associated with an early incidence peak. Airports and railway stations in prefectures significantly advanced arrival days but had no significant impact on peak days. The pandemic spread across mainland China from the southeast to the northwest in two phases that were split at approximately 1 August 2009. Both air and road travel played a significant role in accelerating the spread during phases I and II, but rail travel was only significant during phase II. In conclusion, in addition to air and road travel, rail travel also played a significant role in accelerating influenza A(H1N1)pdm09 spread between prefectures. Establishing a multiscale mobility network that considers the competitive advantage of rail travel for mid to long distances is essential for understanding the influenza pandemic transmission in China.
Url:
DOI: 10.3390/ijerph16020222
PubMed: 30646629
PubMed Central: 6352022
Affiliations:
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PMC:6352022Le document en format XML
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100875</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Chan, Karen Kie Yan" sort="Chan, Karen Kie Yan" uniqKey="Chan K" first="Karen Kie Yan" last="Chan">Karen Kie Yan Chan</name><affiliation><nlm:aff id="af1-ijerph-16-00222">Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China;<email>cai-j12@mails.tsinghua.edu.cn</email> (J.C.);<email>xu-b15@mails.tsinghua.edu.cn</email> (B.X.);<email>cqe15@mails.tsinghua.edu.cn</email> (K.K.Y.C.)</nlm:aff></affiliation><affiliation wicri:level="1"><nlm:aff id="af2-ijerph-16-00222">Joint Center for Global Change Studies, Beijing 100875, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Joint Center for Global Change Studies, Beijing 100875</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Zhang, Xueying" sort="Zhang, Xueying" uniqKey="Zhang X" first="Xueying" last="Zhang">Xueying Zhang</name><affiliation><nlm:aff id="af3-ijerph-16-00222">Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;<email>xueying.zhang@mssm.edu</email></nlm:aff></affiliation></author><author><name sortKey="Zhang, Bing" sort="Zhang, Bing" uniqKey="Zhang B" first="Bing" last="Zhang">Bing Zhang</name><affiliation><nlm:aff id="af4-ijerph-16-00222">School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China;<email>zhangbing4502431@outlook.com</email></nlm:aff></affiliation></author><author><name sortKey="Chen, Ziyue" sort="Chen, Ziyue" uniqKey="Chen Z" first="Ziyue" last="Chen">Ziyue Chen</name><affiliation><nlm:aff id="af5-ijerph-16-00222">State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China;<email>zychen@bnu.edu.cn</email></nlm:aff></affiliation></author><author><name sortKey="Xu, Bing" sort="Xu, Bing" uniqKey="Xu B" first="Bing" last="Xu">Bing Xu</name><affiliation><nlm:aff id="af1-ijerph-16-00222">Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China;<email>cai-j12@mails.tsinghua.edu.cn</email> (J.C.);<email>xu-b15@mails.tsinghua.edu.cn</email> (B.X.);<email>cqe15@mails.tsinghua.edu.cn</email> (K.K.Y.C.)</nlm:aff></affiliation><affiliation wicri:level="1"><nlm:aff id="af2-ijerph-16-00222">Joint Center for Global Change Studies, Beijing 100875, China</nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Joint Center for Global Change Studies, Beijing 100875</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author></analytic><series><title level="j">International Journal of Environmental Research and Public Health</title><idno type="ISSN">1661-7827</idno><idno type="eISSN">1660-4601</idno><imprint><date when="2019">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>China (epidemiology)</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (transmission)</term><term>Transportation</term><term>Transportation Facilities</term><term>Travel</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Chine (épidémiologie)</term><term>Grippe humaine (transmission)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Réseaux de transports</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Transports</term><term>Voyage</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Chine</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Humans</term><term>Influenza A Virus, H1N1 Subtype</term><term>Transportation</term><term>Transportation Facilities</term><term>Travel</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Humains</term><term>Réseaux de transports</term><term>Sous-type H1N1 du virus de la grippe A</term><term>Transports</term><term>Voyage</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>There is increasing concern about another influenza pandemic in China. However, the understanding of the roles of transport modes in the 2009 influenza A(H1N1) pandemic spread across mainland China is limited. Herein, we collected 127,797 laboratory-confirmed cases of influenza A(H1N1)pdm09 in mainland China from May 2009 to April 2010. Arrival days and peak days were calculated for all 340 prefectures to characterize the dissemination patterns of the pandemic. We first evaluated the effects of airports and railway stations on arrival days and peak days, and then we applied quantile regressions to quantify the relationships between arrival days and air, rail, and road travel. Our results showed that early arrival of the virus was not associated with an early incidence peak. Airports and railway stations in prefectures significantly advanced arrival days but had no significant impact on peak days. The pandemic spread across mainland China from the southeast to the northwest in two phases that were split at approximately 1 August 2009. Both air and road travel played a significant role in accelerating the spread during phases I and II, but rail travel was only significant during phase II. In conclusion, in addition to air and road travel, rail travel also played a significant role in accelerating influenza A(H1N1)pdm09 spread between prefectures. Establishing a multiscale mobility network that considers the competitive advantage of rail travel for mid to long distances is essential for understanding the influenza pandemic transmission in China.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Dawood, F S" uniqKey="Dawood F">F.S. Dawood</name></author><author><name sortKey="Iuliano, A D" uniqKey="Iuliano A">A.D. Iuliano</name></author><author><name sortKey="Reed, C" uniqKey="Reed C">C. 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Grenfell</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Pékin</li></settlement></list><tree><noCountry><name sortKey="Chen, Ziyue" sort="Chen, Ziyue" uniqKey="Chen Z" first="Ziyue" last="Chen">Ziyue Chen</name><name sortKey="Zhang, Bing" sort="Zhang, Bing" uniqKey="Zhang B" first="Bing" last="Zhang">Bing Zhang</name><name sortKey="Zhang, Xueying" sort="Zhang, Xueying" uniqKey="Zhang X" first="Xueying" last="Zhang">Xueying Zhang</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Cai, Jun" sort="Cai, Jun" uniqKey="Cai J" first="Jun" last="Cai">Jun Cai</name></noRegion><name sortKey="Chan, Karen Kie Yan" sort="Chan, Karen Kie Yan" uniqKey="Chan K" first="Karen Kie Yan" last="Chan">Karen Kie Yan Chan</name><name sortKey="Xu, Bing" sort="Xu, Bing" uniqKey="Xu B" first="Bing" last="Xu">Bing Xu</name><name sortKey="Xu, Bo" sort="Xu, Bo" uniqKey="Xu B" first="Bo" last="Xu">Bo Xu</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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