Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries

The coronavirus pandemic has not only gripped the scientific community in the search for a vaccine or a cure but also in attempts using statistics and association analysis—to identify environmental factors that increase its potency. A study by Ogen (Sci Total Environ 726:138605, 2020a) explored the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Earth systems and environment 2020-09, Vol.4 (3), p.513-522
Hauptverfasser: Li, Wenzhao, Thomas, Rejoice, El-Askary, Hesham, Piechota, Thomas, Struppa, Daniele, Abdel Ghaffar, Khaled A.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 522
container_issue 3
container_start_page 513
container_title Earth systems and environment
container_volume 4
creator Li, Wenzhao
Thomas, Rejoice
El-Askary, Hesham
Piechota, Thomas
Struppa, Daniele
Abdel Ghaffar, Khaled A.
description The coronavirus pandemic has not only gripped the scientific community in the search for a vaccine or a cure but also in attempts using statistics and association analysis—to identify environmental factors that increase its potency. A study by Ogen (Sci Total Environ 726:138605, 2020a) explored the possible correlation between coronavirus fatality and high nitrogen dioxide exposure in four European countries—France, Germany, Italy and Spain. Meanwhile, another study showed the importance of nitrogen dioxide along with population density in determining the coronavirus pandemic rate in England. In this follow-up study, Aerosol Optical Depth (AOD) was introduced in conjunction with other variables like nitrogen dioxide and population density for further analysis in fifty-four administrative regions of Germany, Italy and Spain. The AOD values were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites while the nitrogen dioxide data were extracted from TROPOMI (TROPOspheric Monitoring Instrument) sensor onboard the Sentinel-5 Precursor satellite. Regression models, as well as multiple statistical tests were used to evaluate the predictive skill and significance of each variable to the fatality rate. The study was conducted for two periods: (1) pre-exposure period (Dec 1, 2019–Feb 29, 2020); (2) complete exposure period (Dec 1, 2019–Jul 1, 2020). Some of the results pointed towards AOD potentially being a factor in estimating the coronavirus fatality rate. The models performed better using the data collected during the complete exposure period, which showed higher AOD values contributed to an increased significance of AOD in the models. Meanwhile, some uncertainties of the analytical results could be attributed to data quality and the absence of other important factors that determine the coronavirus fatality rate.
doi_str_mv 10.1007/s41748-020-00176-4
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7502156</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2591215575</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-61222184528497ac84ccc7fd3e110785e3446bb8619c595977f2e90ae236a1483</originalsourceid><addsrcrecordid>eNp9kV1LHDEUhkNpqaL-gV6UQG96MzWfk8lNYdlqKwhCa69DNp6Zjcwka5JZ8N83dXW1XvTqHDjPec_Hi9AHSr5QQtRpFlSJriGMNIRQ1TbiDTpkkuhGCy7e7nPWHqCTnP2KcMpazph-jw64UIwTxQ_R9iJsIRc_2OLDgMsa8C8_BN97Z4MDHHu8gBRzHDP2AX-DAmny4YldxhSD3fo0Z3xuix19ucc_bQG8mGJlrtcJAJ_NKW7AhorPoSQP-Ri96-2Y4eQxHqHf52fXyx_N5dX3i-XisnFCidK0lDFGOyFZJ7SyrhPOOdXfcKCUqE4CF6JdrbqWaie11Er1DDSxwHhrqej4Efq6093MqwluHNTxdjSb5Ceb7k203vxbCX5thrg1ShJGZVsFPj8KpHg310-ZyWcH42gDxDkbJjWtoFSyop9eobdxTqGeZ5jmnBPJHyi2o1z9ak7Q75ehxPx11uycNdVZ8-CsEbXp48sz9i1PPlaA74BcS2GA9Dz7P7J_AOrRr0Q</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2933305375</pqid></control><display><type>article</type><title>Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries</title><source>SpringerLink Journals</source><source>ProQuest Central</source><creator>Li, Wenzhao ; Thomas, Rejoice ; El-Askary, Hesham ; Piechota, Thomas ; Struppa, Daniele ; Abdel Ghaffar, Khaled A.</creator><creatorcontrib>Li, Wenzhao ; Thomas, Rejoice ; El-Askary, Hesham ; Piechota, Thomas ; Struppa, Daniele ; Abdel Ghaffar, Khaled A.</creatorcontrib><description>The coronavirus pandemic has not only gripped the scientific community in the search for a vaccine or a cure but also in attempts using statistics and association analysis—to identify environmental factors that increase its potency. A study by Ogen (Sci Total Environ 726:138605, 2020a) explored the possible correlation between coronavirus fatality and high nitrogen dioxide exposure in four European countries—France, Germany, Italy and Spain. Meanwhile, another study showed the importance of nitrogen dioxide along with population density in determining the coronavirus pandemic rate in England. In this follow-up study, Aerosol Optical Depth (AOD) was introduced in conjunction with other variables like nitrogen dioxide and population density for further analysis in fifty-four administrative regions of Germany, Italy and Spain. The AOD values were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites while the nitrogen dioxide data were extracted from TROPOMI (TROPOspheric Monitoring Instrument) sensor onboard the Sentinel-5 Precursor satellite. Regression models, as well as multiple statistical tests were used to evaluate the predictive skill and significance of each variable to the fatality rate. The study was conducted for two periods: (1) pre-exposure period (Dec 1, 2019–Feb 29, 2020); (2) complete exposure period (Dec 1, 2019–Jul 1, 2020). Some of the results pointed towards AOD potentially being a factor in estimating the coronavirus fatality rate. The models performed better using the data collected during the complete exposure period, which showed higher AOD values contributed to an increased significance of AOD in the models. Meanwhile, some uncertainties of the analytical results could be attributed to data quality and the absence of other important factors that determine the coronavirus fatality rate.</description><identifier>ISSN: 2509-9426</identifier><identifier>EISSN: 2509-9434</identifier><identifier>DOI: 10.1007/s41748-020-00176-4</identifier><identifier>PMID: 34723073</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Aerosols ; Air pollution ; Association analysis ; Climate ; Climate Change/Climate Change Impacts ; Coronaviruses ; COVID-19 ; COVID-19 vaccines ; Disease transmission ; Earth and Environmental Science ; Earth Sciences ; Earth System Sciences ; Environmental factors ; Environmental Science and Engineering ; Exposure ; Fatalities ; Geography ; Hypotheses ; Investigations ; Monitoring instruments ; Monitoring/Environmental Analysis ; Mortality ; Nitrogen dioxide ; Optical analysis ; Optical thickness ; Original ; Original Article ; Outdoor air quality ; Pandemics ; Pollutants ; Population density ; Regression analysis ; Regression models ; Spectroradiometers ; Statistical analysis ; Statistical tests ; Variables</subject><ispartof>Earth systems and environment, 2020-09, Vol.4 (3), p.513-522</ispartof><rights>The Author(s) 2020</rights><rights>The Author(s) 2020.</rights><rights>The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-61222184528497ac84ccc7fd3e110785e3446bb8619c595977f2e90ae236a1483</citedby><cites>FETCH-LOGICAL-c474t-61222184528497ac84ccc7fd3e110785e3446bb8619c595977f2e90ae236a1483</cites><orcidid>0000-0002-9876-3705</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s41748-020-00176-4$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2933305375?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,776,780,881,21367,27901,27902,33721,33722,41464,42533,43781,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34723073$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Wenzhao</creatorcontrib><creatorcontrib>Thomas, Rejoice</creatorcontrib><creatorcontrib>El-Askary, Hesham</creatorcontrib><creatorcontrib>Piechota, Thomas</creatorcontrib><creatorcontrib>Struppa, Daniele</creatorcontrib><creatorcontrib>Abdel Ghaffar, Khaled A.</creatorcontrib><title>Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries</title><title>Earth systems and environment</title><addtitle>Earth Syst Environ</addtitle><addtitle>Earth Syst Environ</addtitle><description>The coronavirus pandemic has not only gripped the scientific community in the search for a vaccine or a cure but also in attempts using statistics and association analysis—to identify environmental factors that increase its potency. A study by Ogen (Sci Total Environ 726:138605, 2020a) explored the possible correlation between coronavirus fatality and high nitrogen dioxide exposure in four European countries—France, Germany, Italy and Spain. Meanwhile, another study showed the importance of nitrogen dioxide along with population density in determining the coronavirus pandemic rate in England. In this follow-up study, Aerosol Optical Depth (AOD) was introduced in conjunction with other variables like nitrogen dioxide and population density for further analysis in fifty-four administrative regions of Germany, Italy and Spain. The AOD values were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites while the nitrogen dioxide data were extracted from TROPOMI (TROPOspheric Monitoring Instrument) sensor onboard the Sentinel-5 Precursor satellite. Regression models, as well as multiple statistical tests were used to evaluate the predictive skill and significance of each variable to the fatality rate. The study was conducted for two periods: (1) pre-exposure period (Dec 1, 2019–Feb 29, 2020); (2) complete exposure period (Dec 1, 2019–Jul 1, 2020). Some of the results pointed towards AOD potentially being a factor in estimating the coronavirus fatality rate. The models performed better using the data collected during the complete exposure period, which showed higher AOD values contributed to an increased significance of AOD in the models. Meanwhile, some uncertainties of the analytical results could be attributed to data quality and the absence of other important factors that determine the coronavirus fatality rate.</description><subject>Aerosols</subject><subject>Air pollution</subject><subject>Association analysis</subject><subject>Climate</subject><subject>Climate Change/Climate Change Impacts</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>COVID-19 vaccines</subject><subject>Disease transmission</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth System Sciences</subject><subject>Environmental factors</subject><subject>Environmental Science and Engineering</subject><subject>Exposure</subject><subject>Fatalities</subject><subject>Geography</subject><subject>Hypotheses</subject><subject>Investigations</subject><subject>Monitoring instruments</subject><subject>Monitoring/Environmental Analysis</subject><subject>Mortality</subject><subject>Nitrogen dioxide</subject><subject>Optical analysis</subject><subject>Optical thickness</subject><subject>Original</subject><subject>Original Article</subject><subject>Outdoor air quality</subject><subject>Pandemics</subject><subject>Pollutants</subject><subject>Population density</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Spectroradiometers</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>Variables</subject><issn>2509-9426</issn><issn>2509-9434</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kV1LHDEUhkNpqaL-gV6UQG96MzWfk8lNYdlqKwhCa69DNp6Zjcwka5JZ8N83dXW1XvTqHDjPec_Hi9AHSr5QQtRpFlSJriGMNIRQ1TbiDTpkkuhGCy7e7nPWHqCTnP2KcMpazph-jw64UIwTxQ_R9iJsIRc_2OLDgMsa8C8_BN97Z4MDHHu8gBRzHDP2AX-DAmny4YldxhSD3fo0Z3xuix19ucc_bQG8mGJlrtcJAJ_NKW7AhorPoSQP-Ri96-2Y4eQxHqHf52fXyx_N5dX3i-XisnFCidK0lDFGOyFZJ7SyrhPOOdXfcKCUqE4CF6JdrbqWaie11Er1DDSxwHhrqej4Efq6093MqwluHNTxdjSb5Ceb7k203vxbCX5thrg1ShJGZVsFPj8KpHg310-ZyWcH42gDxDkbJjWtoFSyop9eobdxTqGeZ5jmnBPJHyi2o1z9ak7Q75ehxPx11uycNdVZ8-CsEbXp48sz9i1PPlaA74BcS2GA9Dz7P7J_AOrRr0Q</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Li, Wenzhao</creator><creator>Thomas, Rejoice</creator><creator>El-Askary, Hesham</creator><creator>Piechota, Thomas</creator><creator>Struppa, Daniele</creator><creator>Abdel Ghaffar, Khaled A.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9876-3705</orcidid></search><sort><creationdate>20200901</creationdate><title>Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries</title><author>Li, Wenzhao ; Thomas, Rejoice ; El-Askary, Hesham ; Piechota, Thomas ; Struppa, Daniele ; Abdel Ghaffar, Khaled A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-61222184528497ac84ccc7fd3e110785e3446bb8619c595977f2e90ae236a1483</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aerosols</topic><topic>Air pollution</topic><topic>Association analysis</topic><topic>Climate</topic><topic>Climate Change/Climate Change Impacts</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 vaccines</topic><topic>Disease transmission</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Earth System Sciences</topic><topic>Environmental factors</topic><topic>Environmental Science and Engineering</topic><topic>Exposure</topic><topic>Fatalities</topic><topic>Geography</topic><topic>Hypotheses</topic><topic>Investigations</topic><topic>Monitoring instruments</topic><topic>Monitoring/Environmental Analysis</topic><topic>Mortality</topic><topic>Nitrogen dioxide</topic><topic>Optical analysis</topic><topic>Optical thickness</topic><topic>Original</topic><topic>Original Article</topic><topic>Outdoor air quality</topic><topic>Pandemics</topic><topic>Pollutants</topic><topic>Population density</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Spectroradiometers</topic><topic>Statistical analysis</topic><topic>Statistical tests</topic><topic>Variables</topic><toplevel>online_resources</toplevel><creatorcontrib>Li, Wenzhao</creatorcontrib><creatorcontrib>Thomas, Rejoice</creatorcontrib><creatorcontrib>El-Askary, Hesham</creatorcontrib><creatorcontrib>Piechota, Thomas</creatorcontrib><creatorcontrib>Struppa, Daniele</creatorcontrib><creatorcontrib>Abdel Ghaffar, Khaled A.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural &amp; Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric &amp; Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric &amp; Aquatic Science 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>Environmental Science Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Earth systems and environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Wenzhao</au><au>Thomas, Rejoice</au><au>El-Askary, Hesham</au><au>Piechota, Thomas</au><au>Struppa, Daniele</au><au>Abdel Ghaffar, Khaled A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries</atitle><jtitle>Earth systems and environment</jtitle><stitle>Earth Syst Environ</stitle><addtitle>Earth Syst Environ</addtitle><date>2020-09-01</date><risdate>2020</risdate><volume>4</volume><issue>3</issue><spage>513</spage><epage>522</epage><pages>513-522</pages><issn>2509-9426</issn><eissn>2509-9434</eissn><abstract>The coronavirus pandemic has not only gripped the scientific community in the search for a vaccine or a cure but also in attempts using statistics and association analysis—to identify environmental factors that increase its potency. A study by Ogen (Sci Total Environ 726:138605, 2020a) explored the possible correlation between coronavirus fatality and high nitrogen dioxide exposure in four European countries—France, Germany, Italy and Spain. Meanwhile, another study showed the importance of nitrogen dioxide along with population density in determining the coronavirus pandemic rate in England. In this follow-up study, Aerosol Optical Depth (AOD) was introduced in conjunction with other variables like nitrogen dioxide and population density for further analysis in fifty-four administrative regions of Germany, Italy and Spain. The AOD values were extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites while the nitrogen dioxide data were extracted from TROPOMI (TROPOspheric Monitoring Instrument) sensor onboard the Sentinel-5 Precursor satellite. Regression models, as well as multiple statistical tests were used to evaluate the predictive skill and significance of each variable to the fatality rate. The study was conducted for two periods: (1) pre-exposure period (Dec 1, 2019–Feb 29, 2020); (2) complete exposure period (Dec 1, 2019–Jul 1, 2020). Some of the results pointed towards AOD potentially being a factor in estimating the coronavirus fatality rate. The models performed better using the data collected during the complete exposure period, which showed higher AOD values contributed to an increased significance of AOD in the models. Meanwhile, some uncertainties of the analytical results could be attributed to data quality and the absence of other important factors that determine the coronavirus fatality rate.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>34723073</pmid><doi>10.1007/s41748-020-00176-4</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-9876-3705</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2509-9426
ispartof Earth systems and environment, 2020-09, Vol.4 (3), p.513-522
issn 2509-9426
2509-9434
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7502156
source SpringerLink Journals; ProQuest Central
subjects Aerosols
Air pollution
Association analysis
Climate
Climate Change/Climate Change Impacts
Coronaviruses
COVID-19
COVID-19 vaccines
Disease transmission
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Environmental factors
Environmental Science and Engineering
Exposure
Fatalities
Geography
Hypotheses
Investigations
Monitoring instruments
Monitoring/Environmental Analysis
Mortality
Nitrogen dioxide
Optical analysis
Optical thickness
Original
Original Article
Outdoor air quality
Pandemics
Pollutants
Population density
Regression analysis
Regression models
Spectroradiometers
Statistical analysis
Statistical tests
Variables
title Investigating the Significance of Aerosols in Determining the Coronavirus Fatality Rate Among Three European Countries
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-11T15%3A12%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Investigating%20the%20Significance%20of%20Aerosols%20in%20Determining%20the%20Coronavirus%20Fatality%20Rate%20Among%20Three%20European%20Countries&rft.jtitle=Earth%20systems%20and%20environment&rft.au=Li,%20Wenzhao&rft.date=2020-09-01&rft.volume=4&rft.issue=3&rft.spage=513&rft.epage=522&rft.pages=513-522&rft.issn=2509-9426&rft.eissn=2509-9434&rft_id=info:doi/10.1007/s41748-020-00176-4&rft_dat=%3Cproquest_pubme%3E2591215575%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2933305375&rft_id=info:pmid/34723073&rfr_iscdi=true