Climate factors influence seasonal influenza activity in Bangkok, Thailand
Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate...
Gespeichert in:
Veröffentlicht in: | PloS one 2020-09, Vol.15 (9), p.e0239729 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 9 |
container_start_page | e0239729 |
container_title | PloS one |
container_volume | 15 |
creator | Suntronwong, Nungruthai Vichaiwattana, Preeyaporn Klinfueng, Sirapa Korkong, Sumeth Thongmee, Thanunrat Vongpunsawad, Sompong Poovorawan, Yong |
description | Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season. |
doi_str_mv | 10.1371/journal.pone.0239729 |
format | Article |
fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2447246332</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A636883565</galeid><doaj_id>oai_doaj_org_article_8c4d11055951488abab54ffe33f45425</doaj_id><sourcerecordid>A636883565</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-2e1fa0b0b1e58a507c2c7064610453185f9b8f6e6a134193f4a84c7c34d58cb53</originalsourceid><addsrcrecordid>eNqNkl1r1EAUhoMotlb_gWhAEAV3ne9MboS6-LFSKGj1djiZTHannc2smUmx_nonbrZspBeSi4ST57zv-cqypxjNMS3w20vfdy24-da3Zo4ILQtS3suOcUnJTBBE7x98H2WPQrhEiFMpxMPsiJKyxIKi4-zLwtkNRJM3oKPvQm7bxvWm1SYPBoJPDvvQb8gTY69tvEmh_D20qyt_9Sa_WIN10NaPswcNuGCejO-T7PvHDxeLz7Oz80_LxenZTIuSxBkxuAFUoQobLoGjQhNdIMEERoxTLHlTVrIRRgCmLHXQMJBMF5qymktdcXqSPd_pbp0PahxDUISxgjBBKUnEckfUHi7VtksddjfKg1V_A75bKeii1c4oqVmNMeK85JhJCRVUnDWNocmXMzK4vRvd-mpjam3a2IGbiE7_tHatVv5aFTztRIgk8GoU6PzP3oSoNjZo49LIjO93dfNkXQx1v_gHvbu7kVpBaiAtxydfPYiqU0GFlJSLoe75HVR6arOxOt1MY1N8kvB6kpCYaH7FFfQhqOW3r__Pnv-Ysi8P2LUBF9fBuz5a34YpyHag7nwInWluh4yRGk5-Pw01nLwaTz6lPTtc0G3S_sbpH_ca-hY</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2447246332</pqid></control><display><type>article</type><title>Climate factors influence seasonal influenza activity in Bangkok, Thailand</title><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>Public Library of Science (PLoS) Journals Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Suntronwong, Nungruthai ; Vichaiwattana, Preeyaporn ; Klinfueng, Sirapa ; Korkong, Sumeth ; Thongmee, Thanunrat ; Vongpunsawad, Sompong ; Poovorawan, Yong</creator><contributor>Shaman, Jeffrey</contributor><creatorcontrib>Suntronwong, Nungruthai ; Vichaiwattana, Preeyaporn ; Klinfueng, Sirapa ; Korkong, Sumeth ; Thongmee, Thanunrat ; Vongpunsawad, Sompong ; Poovorawan, Yong ; Shaman, Jeffrey</creatorcontrib><description>Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0239729</identifier><identifier>PMID: 32991630</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Annual rainfall ; Biology and life sciences ; Cities ; Climate ; Correlation analysis ; Distribution ; Earth Sciences ; Environmental aspects ; Epidemics ; Generalized linear models ; Geographical locations ; Health planning ; Humans ; Humidity ; Incidence ; Infections ; Influenza ; Influenza A ; Influenza A Virus, H1N1 Subtype - genetics ; Influenza A Virus, H1N1 Subtype - isolation & purification ; Influenza A Virus, H3N2 Subtype - genetics ; Influenza A Virus, H3N2 Subtype - isolation & purification ; Influenza B ; Influenza B virus - genetics ; Influenza B virus - isolation & purification ; Influenza, Human - diagnosis ; Influenza, Human - epidemiology ; Influenza, Human - virology ; Laboratories ; Local climates ; Medical climatology ; Medical research ; Medicine ; Medicine and Health Sciences ; Multivariate Analysis ; Pediatrics ; Physical Sciences ; Public health ; Rain ; Rainfall ; Rainy season ; Real-Time Polymerase Chain Reaction ; Regional climates ; Regions ; Relative humidity ; Research and Analysis Methods ; RNA, Viral - genetics ; RNA, Viral - metabolism ; Seasonal variations ; Seasons ; Sentinel surveillance ; Temperature ; Thailand - epidemiology ; Time series ; Vaccination ; Virology ; Viruses</subject><ispartof>PloS one, 2020-09, Vol.15 (9), p.e0239729</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Suntronwong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Suntronwong et al 2020 Suntronwong et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-2e1fa0b0b1e58a507c2c7064610453185f9b8f6e6a134193f4a84c7c34d58cb53</citedby><cites>FETCH-LOGICAL-c692t-2e1fa0b0b1e58a507c2c7064610453185f9b8f6e6a134193f4a84c7c34d58cb53</cites><orcidid>0000-0002-2337-6807</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523966/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523966/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2097,2916,23848,27906,27907,53773,53775,79350,79351</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32991630$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Shaman, Jeffrey</contributor><creatorcontrib>Suntronwong, Nungruthai</creatorcontrib><creatorcontrib>Vichaiwattana, Preeyaporn</creatorcontrib><creatorcontrib>Klinfueng, Sirapa</creatorcontrib><creatorcontrib>Korkong, Sumeth</creatorcontrib><creatorcontrib>Thongmee, Thanunrat</creatorcontrib><creatorcontrib>Vongpunsawad, Sompong</creatorcontrib><creatorcontrib>Poovorawan, Yong</creatorcontrib><title>Climate factors influence seasonal influenza activity in Bangkok, Thailand</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.</description><subject>Annual rainfall</subject><subject>Biology and life sciences</subject><subject>Cities</subject><subject>Climate</subject><subject>Correlation analysis</subject><subject>Distribution</subject><subject>Earth Sciences</subject><subject>Environmental aspects</subject><subject>Epidemics</subject><subject>Generalized linear models</subject><subject>Geographical locations</subject><subject>Health planning</subject><subject>Humans</subject><subject>Humidity</subject><subject>Incidence</subject><subject>Infections</subject><subject>Influenza</subject><subject>Influenza A</subject><subject>Influenza A Virus, H1N1 Subtype - genetics</subject><subject>Influenza A Virus, H1N1 Subtype - isolation & purification</subject><subject>Influenza A Virus, H3N2 Subtype - genetics</subject><subject>Influenza A Virus, H3N2 Subtype - isolation & purification</subject><subject>Influenza B</subject><subject>Influenza B virus - genetics</subject><subject>Influenza B virus - isolation & purification</subject><subject>Influenza, Human - diagnosis</subject><subject>Influenza, Human - epidemiology</subject><subject>Influenza, Human - virology</subject><subject>Laboratories</subject><subject>Local climates</subject><subject>Medical climatology</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Multivariate Analysis</subject><subject>Pediatrics</subject><subject>Physical Sciences</subject><subject>Public health</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainy season</subject><subject>Real-Time Polymerase Chain Reaction</subject><subject>Regional climates</subject><subject>Regions</subject><subject>Relative humidity</subject><subject>Research and Analysis Methods</subject><subject>RNA, Viral - genetics</subject><subject>RNA, Viral - metabolism</subject><subject>Seasonal variations</subject><subject>Seasons</subject><subject>Sentinel surveillance</subject><subject>Temperature</subject><subject>Thailand - epidemiology</subject><subject>Time series</subject><subject>Vaccination</subject><subject>Virology</subject><subject>Viruses</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkl1r1EAUhoMotlb_gWhAEAV3ne9MboS6-LFSKGj1djiZTHannc2smUmx_nonbrZspBeSi4ST57zv-cqypxjNMS3w20vfdy24-da3Zo4ILQtS3suOcUnJTBBE7x98H2WPQrhEiFMpxMPsiJKyxIKi4-zLwtkNRJM3oKPvQm7bxvWm1SYPBoJPDvvQb8gTY69tvEmh_D20qyt_9Sa_WIN10NaPswcNuGCejO-T7PvHDxeLz7Oz80_LxenZTIuSxBkxuAFUoQobLoGjQhNdIMEERoxTLHlTVrIRRgCmLHXQMJBMF5qymktdcXqSPd_pbp0PahxDUISxgjBBKUnEckfUHi7VtksddjfKg1V_A75bKeii1c4oqVmNMeK85JhJCRVUnDWNocmXMzK4vRvd-mpjam3a2IGbiE7_tHatVv5aFTztRIgk8GoU6PzP3oSoNjZo49LIjO93dfNkXQx1v_gHvbu7kVpBaiAtxydfPYiqU0GFlJSLoe75HVR6arOxOt1MY1N8kvB6kpCYaH7FFfQhqOW3r__Pnv-Ysi8P2LUBF9fBuz5a34YpyHag7nwInWluh4yRGk5-Pw01nLwaTz6lPTtc0G3S_sbpH_ca-hY</recordid><startdate>20200929</startdate><enddate>20200929</enddate><creator>Suntronwong, Nungruthai</creator><creator>Vichaiwattana, Preeyaporn</creator><creator>Klinfueng, Sirapa</creator><creator>Korkong, Sumeth</creator><creator>Thongmee, Thanunrat</creator><creator>Vongpunsawad, Sompong</creator><creator>Poovorawan, Yong</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2337-6807</orcidid></search><sort><creationdate>20200929</creationdate><title>Climate factors influence seasonal influenza activity in Bangkok, Thailand</title><author>Suntronwong, Nungruthai ; Vichaiwattana, Preeyaporn ; Klinfueng, Sirapa ; Korkong, Sumeth ; Thongmee, Thanunrat ; Vongpunsawad, Sompong ; Poovorawan, Yong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-2e1fa0b0b1e58a507c2c7064610453185f9b8f6e6a134193f4a84c7c34d58cb53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Annual rainfall</topic><topic>Biology and life sciences</topic><topic>Cities</topic><topic>Climate</topic><topic>Correlation analysis</topic><topic>Distribution</topic><topic>Earth Sciences</topic><topic>Environmental aspects</topic><topic>Epidemics</topic><topic>Generalized linear models</topic><topic>Geographical locations</topic><topic>Health planning</topic><topic>Humans</topic><topic>Humidity</topic><topic>Incidence</topic><topic>Infections</topic><topic>Influenza</topic><topic>Influenza A</topic><topic>Influenza A Virus, H1N1 Subtype - genetics</topic><topic>Influenza A Virus, H1N1 Subtype - isolation & purification</topic><topic>Influenza A Virus, H3N2 Subtype - genetics</topic><topic>Influenza A Virus, H3N2 Subtype - isolation & purification</topic><topic>Influenza B</topic><topic>Influenza B virus - genetics</topic><topic>Influenza B virus - isolation & purification</topic><topic>Influenza, Human - diagnosis</topic><topic>Influenza, Human - epidemiology</topic><topic>Influenza, Human - virology</topic><topic>Laboratories</topic><topic>Local climates</topic><topic>Medical climatology</topic><topic>Medical research</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Multivariate Analysis</topic><topic>Pediatrics</topic><topic>Physical Sciences</topic><topic>Public health</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Rainy season</topic><topic>Real-Time Polymerase Chain Reaction</topic><topic>Regional climates</topic><topic>Regions</topic><topic>Relative humidity</topic><topic>Research and Analysis Methods</topic><topic>RNA, Viral - genetics</topic><topic>RNA, Viral - metabolism</topic><topic>Seasonal variations</topic><topic>Seasons</topic><topic>Sentinel surveillance</topic><topic>Temperature</topic><topic>Thailand - epidemiology</topic><topic>Time series</topic><topic>Vaccination</topic><topic>Virology</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suntronwong, Nungruthai</creatorcontrib><creatorcontrib>Vichaiwattana, Preeyaporn</creatorcontrib><creatorcontrib>Klinfueng, Sirapa</creatorcontrib><creatorcontrib>Korkong, Sumeth</creatorcontrib><creatorcontrib>Thongmee, Thanunrat</creatorcontrib><creatorcontrib>Vongpunsawad, Sompong</creatorcontrib><creatorcontrib>Poovorawan, Yong</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suntronwong, Nungruthai</au><au>Vichaiwattana, Preeyaporn</au><au>Klinfueng, Sirapa</au><au>Korkong, Sumeth</au><au>Thongmee, Thanunrat</au><au>Vongpunsawad, Sompong</au><au>Poovorawan, Yong</au><au>Shaman, Jeffrey</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Climate factors influence seasonal influenza activity in Bangkok, Thailand</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-09-29</date><risdate>2020</risdate><volume>15</volume><issue>9</issue><spage>e0239729</spage><pages>e0239729-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Yearly increase in influenza activity is associated with cold and dry winter in the temperate regions, while influenza patterns in tropical countries vary significantly by regional climates and geographic locations. To examine the association between influenza activity in Thailand and local climate factors including temperature, relative humidity, and rainfall, we analyzed the influenza surveillance data from January 2010 to December 2018 obtained from a large private hospital in Bangkok. We found that approximately one in five influenza-like illness samples (21.6% or 6,678/30,852) tested positive for influenza virus. Influenza virus typing showed that 34.2% were influenza A(H1N1)pdm09, 46.0% were influenza A(H3N2), and 19.8% were influenza B virus. There were two seasonal waves of increased influenza activity. Peak influenza A(H1N1)pdm09 activity occurred in February and again in August, while influenza A(H3N2) and influenza B viruses were primarily detected in August and September. Time series analysis suggests that increased relative humidity was significantly associated with increased influenza activity in Bangkok. Months with peak influenza activity generally followed the most humid months of the year. We performed the seasonal autoregressive integrated moving average (SARIMA) multivariate analysis of all influenza activity on the 2011 to 2017 data to predict the influenza activity for 2018. The resulting model closely resembled the actual observed overall influenza detected that year. Consequently, the ability to predict seasonal pattern of influenza in a large tropical city such as Bangkok may enable better public health planning and underscores the importance of annual influenza vaccination prior to the rainy season.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32991630</pmid><doi>10.1371/journal.pone.0239729</doi><tpages>e0239729</tpages><orcidid>https://orcid.org/0000-0002-2337-6807</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1932-6203 |
ispartof | PloS one, 2020-09, Vol.15 (9), p.e0239729 |
issn | 1932-6203 1932-6203 |
language | eng |
recordid | cdi_plos_journals_2447246332 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Annual rainfall Biology and life sciences Cities Climate Correlation analysis Distribution Earth Sciences Environmental aspects Epidemics Generalized linear models Geographical locations Health planning Humans Humidity Incidence Infections Influenza Influenza A Influenza A Virus, H1N1 Subtype - genetics Influenza A Virus, H1N1 Subtype - isolation & purification Influenza A Virus, H3N2 Subtype - genetics Influenza A Virus, H3N2 Subtype - isolation & purification Influenza B Influenza B virus - genetics Influenza B virus - isolation & purification Influenza, Human - diagnosis Influenza, Human - epidemiology Influenza, Human - virology Laboratories Local climates Medical climatology Medical research Medicine Medicine and Health Sciences Multivariate Analysis Pediatrics Physical Sciences Public health Rain Rainfall Rainy season Real-Time Polymerase Chain Reaction Regional climates Regions Relative humidity Research and Analysis Methods RNA, Viral - genetics RNA, Viral - metabolism Seasonal variations Seasons Sentinel surveillance Temperature Thailand - epidemiology Time series Vaccination Virology Viruses |
title | Climate factors influence seasonal influenza activity in Bangkok, Thailand |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T09%3A26%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Climate%20factors%20influence%20seasonal%20influenza%20activity%20in%20Bangkok,%20Thailand&rft.jtitle=PloS%20one&rft.au=Suntronwong,%20Nungruthai&rft.date=2020-09-29&rft.volume=15&rft.issue=9&rft.spage=e0239729&rft.pages=e0239729-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0239729&rft_dat=%3Cgale_plos_%3EA636883565%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2447246332&rft_id=info:pmid/32991630&rft_galeid=A636883565&rft_doaj_id=oai_doaj_org_article_8c4d11055951488abab54ffe33f45425&rfr_iscdi=true |