Assessing Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19.
Identifieur interne : 000104 ( Main/Exploration ); précédent : 000103; suivant : 000105Assessing Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19.
Auteurs : Eran Bendavid [États-Unis] ; Christopher Oh [États-Unis] ; Jay Bhattacharya [États-Unis] ; John P A. Ioannidis [États-Unis]Source :
- European journal of clinical investigation [ 1365-2362 ] ; 2021.
Abstract
BACKGROUND AND AIMS
The most restrictive non-pharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).
METHODS
We first estimate COVID-19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden, and the US. Using first-difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, two countries that did not implement mandatory stay-at-home and business closures, as comparison countries for the other 8 countries (16 total comparisons).
RESULTS
Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a non-significant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, e.g., the effect of mrNPIs was +7% (95CI -5%-19%) when compared with Sweden, and +13% (-12%-38%) when compared with South Korea (positive means pro-contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons.
CONCLUSIONS
While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.
DOI: 10.1111/eci.13484
PubMed: 33400268
Affiliations:
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Ioannidis</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Stanford University Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology and Population Health, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Data Science, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Statistics, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.</nlm:affiliation><country 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Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19.</title><author><name sortKey="Bendavid, Eran" sort="Bendavid, Eran" uniqKey="Bendavid E" first="Eran" last="Bendavid">Eran Bendavid</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Stanford University Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation></author><author><name sortKey="Oh, Christopher" sort="Oh, Christopher" uniqKey="Oh C" first="Christopher" last="Oh">Christopher Oh</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Stanford University Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Bhattacharya, Jay" sort="Bhattacharya, Jay" uniqKey="Bhattacharya J" first="Jay" last="Bhattacharya">Jay Bhattacharya</name><affiliation wicri:level="4"><nlm:affiliation>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation></author><author><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><affiliation wicri:level="2"><nlm:affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Medicine, Stanford University Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Epidemiology and Population Health, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Data Science, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Department of Statistics, Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Statistics, Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation><affiliation wicri:level="4"><nlm:affiliation>Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Stanford (Californie)</settlement></placeName><orgName type="university">Université Stanford</orgName></affiliation></author></analytic><series><title level="j">European journal of clinical investigation</title><idno type="eISSN">1365-2362</idno><imprint><date when="2021" type="published">2021</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND AND AIMS</b></p><p>The most restrictive non-pharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We first estimate COVID-19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden, and the US. Using first-difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, two countries that did not implement mandatory stay-at-home and business closures, as comparison countries for the other 8 countries (16 total comparisons).</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a non-significant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, e.g., the effect of mrNPIs was +7% (95CI -5%-19%) when compared with Sweden, and +13% (-12%-38%) when compared with South Korea (positive means pro-contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.</p></div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">33400268</PMID><DateRevised><Year>2021</Year><Month>01</Month><Day>05</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-2362</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2021</Year><Month>Jan</Month><Day>05</Day></PubDate></JournalIssue><Title>European journal of clinical investigation</Title><ISOAbbreviation>Eur J Clin Invest</ISOAbbreviation></Journal><ArticleTitle>Assessing Mandatory Stay-at-Home and Business Closure Effects on the Spread of COVID-19.</ArticleTitle><Pagination><MedlinePgn>e13484</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/eci.13484</ELocationID><Abstract><AbstractText Label="BACKGROUND AND AIMS" NlmCategory="OBJECTIVE">The most restrictive non-pharmaceutical interventions (NPIs) for controlling the spread of COVID-19 are mandatory stay-at-home and business closures. Given the consequences of these policies, it is important to assess their effects. We evaluate the effects on epidemic case growth of more restrictive NPIs (mrNPIs), above and beyond those of less restrictive NPIs (lrNPIs).</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">We first estimate COVID-19 case growth in relation to any NPI implementation in subnational regions of 10 countries: England, France, Germany, Iran, Italy, Netherlands, Spain, South Korea, Sweden, and the US. Using first-difference models with fixed effects, we isolate the effects of mrNPIs by subtracting the combined effects of lrNPIs and epidemic dynamics from all NPIs. We use case growth in Sweden and South Korea, two countries that did not implement mandatory stay-at-home and business closures, as comparison countries for the other 8 countries (16 total comparisons).</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">Implementing any NPIs was associated with significant reductions in case growth in 9 out of 10 study countries, including South Korea and Sweden that implemented only lrNPIs (Spain had a non-significant effect). After subtracting the epidemic and lrNPI effects, we find no clear, significant beneficial effect of mrNPIs on case growth in any country. In France, e.g., the effect of mrNPIs was +7% (95CI -5%-19%) when compared with Sweden, and +13% (-12%-38%) when compared with South Korea (positive means pro-contagion). The 95% confidence intervals excluded 30% declines in all 16 comparisons and 15% declines in 11/16 comparisons.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">While small benefits cannot be excluded, we do not find significant benefits on case growth of more restrictive NPIs. Similar reductions in case growth may be achievable with less restrictive interventions.</AbstractText><CopyrightInformation>This article is protected by copyright. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Bendavid</LastName><ForeName>Eran</ForeName><Initials>E</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-8364-4711</Identifier><AffiliationInfo><Affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Oh</LastName><ForeName>Christopher</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bhattacharya</LastName><ForeName>Jay</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Center for Health Policy and the Center for Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ioannidis</LastName><ForeName>John P A</ForeName><Initials>JPA</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-3118-6859</Identifier><AffiliationInfo><Affiliation>Department of Medicine, Stanford University Stanford, CA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Statistics, Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2021</Year><Month>01</Month><Day>05</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Eur J Clin Invest</MedlineTA><NlmUniqueID>0245331</NlmUniqueID><ISSNLinking>0014-2972</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2021</Year><Month>1</Month><Day>5</Day><Hour>12</Hour><Minute>18</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2021</Year><Month>1</Month><Day>6</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2021</Year><Month>1</Month><Day>6</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33400268</ArticleId><ArticleId IdType="doi">10.1111/eci.13484</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Californie</li></region><settlement><li>Stanford (Californie)</li></settlement><orgName><li>Université Stanford</li></orgName></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Bendavid, Eran" sort="Bendavid, Eran" uniqKey="Bendavid E" first="Eran" last="Bendavid">Eran Bendavid</name></region><name sortKey="Bendavid, Eran" sort="Bendavid, Eran" uniqKey="Bendavid E" first="Eran" last="Bendavid">Eran Bendavid</name><name sortKey="Bhattacharya, Jay" sort="Bhattacharya, Jay" uniqKey="Bhattacharya J" first="Jay" last="Bhattacharya">Jay Bhattacharya</name><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><name sortKey="Ioannidis, John P A" sort="Ioannidis, John P A" uniqKey="Ioannidis J" first="John P A" last="Ioannidis">John P A. Ioannidis</name><name sortKey="Oh, Christopher" sort="Oh, Christopher" uniqKey="Oh C" first="Christopher" last="Oh">Christopher Oh</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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