Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications.
Identifieur interne : 000092 ( Main/Exploration ); précédent : 000091; suivant : 000093Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications.
Auteurs : G. Buonanno [Australie] ; L. Morawska [Australie] ; L. Stabile [Italie]Source :
- Environment international [ 1873-6750 ] ; 2020.
Descripteurs français
- KwdFr :
- Appréciation des risques (méthodes), Aérosols (MeSH), Betacoronavirus (MeSH), Chine (MeSH), Coronavirus (MeSH), Humains (MeSH), Infections à coronavirus (prévention et contrôle), Infections à coronavirus (transmission), Infections à coronavirus (épidémiologie), Pandémies (MeSH), Pneumopathie virale (prévention et contrôle), Pneumopathie virale (transmission), Pneumopathie virale (épidémiologie), Pollution de l'air intérieur (MeSH), Études prospectives (MeSH), Études rétrospectives (MeSH).
- MESH :
- méthodes : Appréciation des risques.
- prévention et contrôle : Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Infections à coronavirus, Pneumopathie virale.
- Aérosols, Betacoronavirus, Chine, Coronavirus, Humains, Pandémies, Pollution de l'air intérieur, Études prospectives, Études rétrospectives.
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- Aerosols (MeSH), Air Pollution, Indoor (MeSH), Betacoronavirus (MeSH), COVID-19 (MeSH), China (MeSH), Coronavirus (MeSH), Coronavirus Infections (epidemiology), Coronavirus Infections (prevention & control), Coronavirus Infections (transmission), Humans (MeSH), Pandemics (MeSH), Pneumonia, Viral (epidemiology), Pneumonia, Viral (prevention & control), Pneumonia, Viral (transmission), Prospective Studies (MeSH), Retrospective Studies (MeSH), Risk Assessment (methods), SARS-CoV-2 (MeSH).
- MESH :
- chemical : Aerosols.
- geographic : China.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- methods : Risk Assessment.
- prevention & control : Coronavirus Infections, Pneumonia, Viral.
- transmission : Coronavirus Infections, Pneumonia, Viral.
- Air Pollution, Indoor, Betacoronavirus, COVID-19, Coronavirus, Humans, Pandemics, Prospective Studies, Retrospective Studies, SARS-CoV-2.
Abstract
Airborne transmission is a recognized pathway of contagion; however, it is rarely quantitatively evaluated. The numerous outbreaks that have occurred during the SARS-CoV-2 pandemic are putting a demand on researchers to develop approaches capable of both predicting contagion in closed environments (predictive assessment) and analyzing previous infections (retrospective assessment). This study presents a novel approach for quantitative assessment of the individual infection risk of susceptible subjects exposed in indoor microenvironments in the presence of an asymptomatic infected SARS-CoV-2 subject. The application of a Monte Carlo method allowed the risk for an exposed healthy subject to be evaluated or, starting from an acceptable risk, the maximum exposure time. We applied the proposed approach to four distinct scenarios for a prospective assessment, highlighting that, in order to guarantee an acceptable risk of 10-3 for exposed subjects in naturally ventilated indoor environments, the exposure time could be well below one hour. Such maximum exposure time clearly depends on the viral load emission of the infected subject and on the exposure conditions; thus, longer exposure times were estimated for mechanically ventilated indoor environments and lower viral load emissions. The proposed approach was used for retrospective assessment of documented outbreaks in a restaurant in Guangzhou (China) and at a choir rehearsal in Mount Vernon (USA), showing that, in both cases, the high attack rate values can be justified only assuming the airborne transmission as the main route of contagion. Moreover, we show that such outbreaks are not caused by the rare presence of a superspreader, but can be likely explained by the co-existence of conditions, including emission and exposure parameters, leading to a highly probable event, which can be defined as a "superspreading event".
DOI: 10.1016/j.envint.2020.106112
PubMed: 32927282
PubMed Central: PMC7474922
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Buonanno</name><affiliation wicri:level="1"><nlm:affiliation>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy; International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy; International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld</wicri:regionArea><wicri:noRegion>Qld</wicri:noRegion></affiliation></author><author><name sortKey="Morawska, L" sort="Morawska, L" uniqKey="Morawska L" first="L" last="Morawska">L. 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Morawska</name><affiliation wicri:level="1"><nlm:affiliation>International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld</wicri:regionArea><wicri:noRegion>Qld</wicri:noRegion></affiliation></author><author><name sortKey="Stabile, L" sort="Stabile, L" uniqKey="Stabile L" first="L" last="Stabile">L. Stabile</name><affiliation wicri:level="1"><nlm:affiliation>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy. Electronic address: l.stabile@unicas.it.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR</wicri:regionArea><wicri:noRegion>FR</wicri:noRegion></affiliation></author></analytic><series><title level="j">Environment international</title><idno type="eISSN">1873-6750</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Aerosols (MeSH)</term><term>Air Pollution, Indoor (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>COVID-19 (MeSH)</term><term>China (MeSH)</term><term>Coronavirus (MeSH)</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (prevention & control)</term><term>Coronavirus Infections (transmission)</term><term>Humans (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (epidemiology)</term><term>Pneumonia, Viral (prevention & control)</term><term>Pneumonia, Viral (transmission)</term><term>Prospective Studies (MeSH)</term><term>Retrospective Studies (MeSH)</term><term>Risk Assessment (methods)</term><term>SARS-CoV-2 (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Appréciation des risques (méthodes)</term><term>Aérosols (MeSH)</term><term>Betacoronavirus (MeSH)</term><term>Chine (MeSH)</term><term>Coronavirus (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (prévention et contrôle)</term><term>Infections à coronavirus (transmission)</term><term>Infections à coronavirus (épidémiologie)</term><term>Pandémies (MeSH)</term><term>Pneumopathie virale (prévention et contrôle)</term><term>Pneumopathie virale (transmission)</term><term>Pneumopathie virale (épidémiologie)</term><term>Pollution de l'air intérieur (MeSH)</term><term>Études prospectives (MeSH)</term><term>Études rétrospectives (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>Aerosols</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Risk Assessment</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Appréciation des risques</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Air Pollution, Indoor</term><term>Betacoronavirus</term><term>COVID-19</term><term>Coronavirus</term><term>Humans</term><term>Pandemics</term><term>Prospective Studies</term><term>Retrospective Studies</term><term>SARS-CoV-2</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Aérosols</term><term>Betacoronavirus</term><term>Chine</term><term>Coronavirus</term><term>Humains</term><term>Pandémies</term><term>Pollution de l'air intérieur</term><term>Études prospectives</term><term>Études rétrospectives</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">Airborne transmission is a recognized pathway of contagion; however, it is rarely quantitatively evaluated. The numerous outbreaks that have occurred during the SARS-CoV-2 pandemic are putting a demand on researchers to develop approaches capable of both predicting contagion in closed environments (predictive assessment) and analyzing previous infections (retrospective assessment). This study presents a novel approach for quantitative assessment of the individual infection risk of susceptible subjects exposed in indoor microenvironments in the presence of an asymptomatic infected SARS-CoV-2 subject. The application of a Monte Carlo method allowed the risk for an exposed healthy subject to be evaluated or, starting from an acceptable risk, the maximum exposure time. We applied the proposed approach to four distinct scenarios for a prospective assessment, highlighting that, in order to guarantee an acceptable risk of 10<sup>-3</sup> for exposed subjects in naturally ventilated indoor environments, the exposure time could be well below one hour. Such maximum exposure time clearly depends on the viral load emission of the infected subject and on the exposure conditions; thus, longer exposure times were estimated for mechanically ventilated indoor environments and lower viral load emissions. The proposed approach was used for retrospective assessment of documented outbreaks in a restaurant in Guangzhou (China) and at a choir rehearsal in Mount Vernon (USA), showing that, in both cases, the high attack rate values can be justified only assuming the airborne transmission as the main route of contagion. Moreover, we show that such outbreaks are not caused by the rare presence of a superspreader, but can be likely explained by the co-existence of conditions, including emission and exposure parameters, leading to a highly probable event, which can be defined as a "superspreading event".</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">32927282</PMID><DateCompleted><Year>2020</Year><Month>10</Month><Day>27</Day></DateCompleted><DateRevised><Year>2020</Year><Month>12</Month><Day>10</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1873-6750</ISSN><JournalIssue CitedMedium="Internet"><Volume>145</Volume><PubDate><Year>2020</Year><Month>12</Month></PubDate></JournalIssue><Title>Environment international</Title><ISOAbbreviation>Environ Int</ISOAbbreviation></Journal><ArticleTitle>Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications.</ArticleTitle><Pagination><MedlinePgn>106112</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0160-4120(20)32067-5</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.envint.2020.106112</ELocationID><Abstract><AbstractText>Airborne transmission is a recognized pathway of contagion; however, it is rarely quantitatively evaluated. The numerous outbreaks that have occurred during the SARS-CoV-2 pandemic are putting a demand on researchers to develop approaches capable of both predicting contagion in closed environments (predictive assessment) and analyzing previous infections (retrospective assessment). This study presents a novel approach for quantitative assessment of the individual infection risk of susceptible subjects exposed in indoor microenvironments in the presence of an asymptomatic infected SARS-CoV-2 subject. The application of a Monte Carlo method allowed the risk for an exposed healthy subject to be evaluated or, starting from an acceptable risk, the maximum exposure time. We applied the proposed approach to four distinct scenarios for a prospective assessment, highlighting that, in order to guarantee an acceptable risk of 10<sup>-3</sup> for exposed subjects in naturally ventilated indoor environments, the exposure time could be well below one hour. Such maximum exposure time clearly depends on the viral load emission of the infected subject and on the exposure conditions; thus, longer exposure times were estimated for mechanically ventilated indoor environments and lower viral load emissions. The proposed approach was used for retrospective assessment of documented outbreaks in a restaurant in Guangzhou (China) and at a choir rehearsal in Mount Vernon (USA), showing that, in both cases, the high attack rate values can be justified only assuming the airborne transmission as the main route of contagion. Moreover, we show that such outbreaks are not caused by the rare presence of a superspreader, but can be likely explained by the co-existence of conditions, including emission and exposure parameters, leading to a highly probable event, which can be defined as a "superspreading event".</AbstractText><CopyrightInformation>Copyright © 2020. Published by Elsevier Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Buonanno</LastName><ForeName>G</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy; International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Morawska</LastName><ForeName>L</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, Qld, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Stabile</LastName><ForeName>L</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino, FR, Italy. 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Buonanno</name></noRegion><name sortKey="Morawska, L" sort="Morawska, L" uniqKey="Morawska L" first="L" last="Morawska">L. Morawska</name></country><country name="Italie"><noRegion><name sortKey="Stabile, L" sort="Stabile, L" uniqKey="Stabile L" first="L" last="Stabile">L. Stabile</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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