Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea
Objectives This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea. Methods We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on s...
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| Veröffentlicht in: | Tropical medicine & international health 2021-04, Vol.26 (4), p.478-491 |
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| creator | Hoang, Tung Nguyen, Trung Quang Tran, Tho Thi Anh |
| description | Objectives
This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea.
Methods
We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model.
Results
We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively).
Conclusions
Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5, CO and SO2 on COVID‐19 infection in two clusters was different. |
| doi_str_mv | 10.1111/tmi.13538 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2507787401</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2507787401</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4168-e855aede5535937e940260a9c354451f70937c8bae95178d042ca472cf32d8803</originalsourceid><addsrcrecordid>eNp1kEtOwzAQhi0EoqWw4ALIEisWae3YzmOJyquiqIsWtpHrOKqrJA62o9IdR-CMnAS3KeyYzYytT9-MfgAuMRpiXyNXqSEmjCRHoI9JxAKCWXS8n1EQhnHUA2fWrhFClLLoFPQIITilGPVBOV9p474_v5w0FZQfjbatkdBpyKulkrWDXBnY6LJsndI1VDXk1mqh-P65UW4Fx7O3yZ1X4BTqArqNhqJsrRfaHT7XrWeetZH8HJwUvLTy4tAH4PXhfjF-Cqazx8n4dhoIiqMkkAljXOaSMcJSEsuUojBCPBWE-ftxESP_K5IllynDcZIjGgpO41AUJMyTBJEBuO68jdHvrbQuW-vW1H5lFjIUx0lMEfbUTUcJo601ssgaoyputhlG2S7XzOea7XP17NXB2C4rmf-Rv0F6YNQBG1XK7f-mbPEy6ZQ_Am2CqQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2507787401</pqid></control><display><type>article</type><title>Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea</title><source>MEDLINE</source><source>Wiley Online Library Free Content</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Access via Wiley Online Library</source><creator>Hoang, Tung ; Nguyen, Trung Quang ; Tran, Tho Thi Anh</creator><creatorcontrib>Hoang, Tung ; Nguyen, Trung Quang ; Tran, Tho Thi Anh</creatorcontrib><description>Objectives
This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea.
Methods
We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model.
Results
We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively).
Conclusions
Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5, CO and SO2 on COVID‐19 infection in two clusters was different.</description><identifier>ISSN: 1360-2276</identifier><identifier>EISSN: 1365-3156</identifier><identifier>DOI: 10.1111/tmi.13538</identifier><identifier>PMID: 33319410</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Air Pollutants - adverse effects ; Air Pollutants - chemistry ; Air pollution ; Air Pollution - adverse effects ; Air temperature ; Carbon monoxide ; Carbon Monoxide - analysis ; Cities ; cluster ; Cluster Analysis ; Clusters ; Confidence intervals ; COVID-19 ; COVID-19 - transmission ; generalised additive model ; Humans ; Meteorological Concepts ; Nitrogen dioxide ; Nitrogen Dioxide - analysis ; Ozone - analysis ; Particulate matter ; Particulate Matter - analysis ; Pollutants ; Republic of Korea - epidemiology ; Risk assessment ; SARS-CoV-2 ; Sulfur dioxide ; Sulfur Dioxide - analysis ; Wind speed</subject><ispartof>Tropical medicine & international health, 2021-04, Vol.26 (4), p.478-491</ispartof><rights>2020 John Wiley & Sons Ltd</rights><rights>2020 John Wiley & Sons Ltd.</rights><rights>2021 John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4168-e855aede5535937e940260a9c354451f70937c8bae95178d042ca472cf32d8803</citedby><cites>FETCH-LOGICAL-c4168-e855aede5535937e940260a9c354451f70937c8bae95178d042ca472cf32d8803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Ftmi.13538$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Ftmi.13538$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33319410$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hoang, Tung</creatorcontrib><creatorcontrib>Nguyen, Trung Quang</creatorcontrib><creatorcontrib>Tran, Tho Thi Anh</creatorcontrib><title>Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea</title><title>Tropical medicine & international health</title><addtitle>Trop Med Int Health</addtitle><description>Objectives
This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea.
Methods
We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model.
Results
We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively).
Conclusions
Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5, CO and SO2 on COVID‐19 infection in two clusters was different.</description><subject>Air Pollutants - adverse effects</subject><subject>Air Pollutants - chemistry</subject><subject>Air pollution</subject><subject>Air Pollution - adverse effects</subject><subject>Air temperature</subject><subject>Carbon monoxide</subject><subject>Carbon Monoxide - analysis</subject><subject>Cities</subject><subject>cluster</subject><subject>Cluster Analysis</subject><subject>Clusters</subject><subject>Confidence intervals</subject><subject>COVID-19</subject><subject>COVID-19 - transmission</subject><subject>generalised additive model</subject><subject>Humans</subject><subject>Meteorological Concepts</subject><subject>Nitrogen dioxide</subject><subject>Nitrogen Dioxide - analysis</subject><subject>Ozone - analysis</subject><subject>Particulate matter</subject><subject>Particulate Matter - analysis</subject><subject>Pollutants</subject><subject>Republic of Korea - epidemiology</subject><subject>Risk assessment</subject><subject>SARS-CoV-2</subject><subject>Sulfur dioxide</subject><subject>Sulfur Dioxide - analysis</subject><subject>Wind speed</subject><issn>1360-2276</issn><issn>1365-3156</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kEtOwzAQhi0EoqWw4ALIEisWae3YzmOJyquiqIsWtpHrOKqrJA62o9IdR-CMnAS3KeyYzYytT9-MfgAuMRpiXyNXqSEmjCRHoI9JxAKCWXS8n1EQhnHUA2fWrhFClLLoFPQIITilGPVBOV9p474_v5w0FZQfjbatkdBpyKulkrWDXBnY6LJsndI1VDXk1mqh-P65UW4Fx7O3yZ1X4BTqArqNhqJsrRfaHT7XrWeetZH8HJwUvLTy4tAH4PXhfjF-Cqazx8n4dhoIiqMkkAljXOaSMcJSEsuUojBCPBWE-ftxESP_K5IllynDcZIjGgpO41AUJMyTBJEBuO68jdHvrbQuW-vW1H5lFjIUx0lMEfbUTUcJo601ssgaoyputhlG2S7XzOea7XP17NXB2C4rmf-Rv0F6YNQBG1XK7f-mbPEy6ZQ_Am2CqQ</recordid><startdate>202104</startdate><enddate>202104</enddate><creator>Hoang, Tung</creator><creator>Nguyen, Trung Quang</creator><creator>Tran, Tho Thi Anh</creator><general>Blackwell Publishing Ltd</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>7T2</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope></search><sort><creationdate>202104</creationdate><title>Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea</title><author>Hoang, Tung ; Nguyen, Trung Quang ; Tran, Tho Thi Anh</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4168-e855aede5535937e940260a9c354451f70937c8bae95178d042ca472cf32d8803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Air Pollutants - adverse effects</topic><topic>Air Pollutants - chemistry</topic><topic>Air pollution</topic><topic>Air Pollution - adverse effects</topic><topic>Air temperature</topic><topic>Carbon monoxide</topic><topic>Carbon Monoxide - analysis</topic><topic>Cities</topic><topic>cluster</topic><topic>Cluster Analysis</topic><topic>Clusters</topic><topic>Confidence intervals</topic><topic>COVID-19</topic><topic>COVID-19 - transmission</topic><topic>generalised additive model</topic><topic>Humans</topic><topic>Meteorological Concepts</topic><topic>Nitrogen dioxide</topic><topic>Nitrogen Dioxide - analysis</topic><topic>Ozone - analysis</topic><topic>Particulate matter</topic><topic>Particulate Matter - analysis</topic><topic>Pollutants</topic><topic>Republic of Korea - epidemiology</topic><topic>Risk assessment</topic><topic>SARS-CoV-2</topic><topic>Sulfur dioxide</topic><topic>Sulfur Dioxide - analysis</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hoang, Tung</creatorcontrib><creatorcontrib>Nguyen, Trung Quang</creatorcontrib><creatorcontrib>Tran, Tho Thi Anh</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><jtitle>Tropical medicine & international health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hoang, Tung</au><au>Nguyen, Trung Quang</au><au>Tran, Tho Thi Anh</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea</atitle><jtitle>Tropical medicine & international health</jtitle><addtitle>Trop Med Int Health</addtitle><date>2021-04</date><risdate>2021</risdate><volume>26</volume><issue>4</issue><spage>478</spage><epage>491</epage><pages>478-491</pages><issn>1360-2276</issn><eissn>1365-3156</eissn><abstract>Objectives
This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea.
Methods
We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model.
Results
We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively).
Conclusions
Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5, CO and SO2 on COVID‐19 infection in two clusters was different.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>33319410</pmid><doi>10.1111/tmi.13538</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Air Pollutants - adverse effects Air Pollutants - chemistry Air pollution Air Pollution - adverse effects Air temperature Carbon monoxide Carbon Monoxide - analysis Cities cluster Cluster Analysis Clusters Confidence intervals COVID-19 COVID-19 - transmission generalised additive model Humans Meteorological Concepts Nitrogen dioxide Nitrogen Dioxide - analysis Ozone - analysis Particulate matter Particulate Matter - analysis Pollutants Republic of Korea - epidemiology Risk assessment SARS-CoV-2 Sulfur dioxide Sulfur Dioxide - analysis Wind speed |
| title | Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea |
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