Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate.
Identifieur interne : 000067 ( Main/Exploration ); précédent : 000066; suivant : 000068Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate.
Auteurs : Charles Courtemanche [États-Unis] ; Joseph Garuccio [Géorgie (pays)] ; Anh Le ; Joshua Pinkston [États-Unis] ; Aaron YelowitzSource :
- Health affairs (Project Hope) [ 1544-5208 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Appréciation des risques (MeSH), Contrôle des maladies transmissibles (organisation et administration), Enfant (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (prévention et contrôle), Infections à coronavirus (épidémiologie), Mâle (MeSH), Pandémies (prévention et contrôle), Pandémies (statistiques et données numériques), Pneumopathie virale (prévention et contrôle), Pneumopathie virale (épidémiologie), Politique de santé (législation et jurisprudence), Processus politique (MeSH), Prévalence (MeSH), Sujet âgé (MeSH), Établissements scolaires (organisation et administration), États-Unis (épidémiologie).
- MESH :
- législation et jurisprudence : Politique de santé.
- organisation et administration : Contrôle des maladies transmissibles, Établissements scolaires.
- prévention et contrôle : Infections à coronavirus, Pandémies, Pneumopathie virale.
- statistiques et données numériques : Pandémies.
- épidémiologie : Infections à coronavirus, Pneumopathie virale, États-Unis.
- Adolescent, Adulte, Adulte d'âge moyen, Appréciation des risques, Enfant, Femelle, Humains, Mâle, Processus politique, Prévalence, Sujet âgé.
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), COVID-19 (MeSH), Child (MeSH), Communicable Disease Control (organization & administration), Coronavirus Infections (epidemiology), Coronavirus Infections (prevention & control), Female (MeSH), Health Policy (legislation & jurisprudence), Humans (MeSH), Male (MeSH), Middle Aged (MeSH), Pandemics (prevention & control), Pandemics (statistics & numerical data), Pneumonia, Viral (epidemiology), Pneumonia, Viral (prevention & control), Policy Making (MeSH), Prevalence (MeSH), Psychological Distance (MeSH), Risk Assessment (MeSH), Schools (organization & administration), United States (epidemiology).
- MESH :
- geographic , epidemiology : United States.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- legislation & jurisprudence : Health Policy.
- organization & administration : Communicable Disease Control, Schools.
- prevention & control : Coronavirus Infections, Pandemics, Pneumonia, Viral.
- statistics & numerical data : Pandemics.
- Adolescent, Adult, Aged, COVID-19, Child, Female, Humans, Male, Middle Aged, Policy Making, Prevalence, Psychological Distance, Risk Assessment.
Abstract
State and local governments imposed social distancing measures in March and April 2020 to contain the spread of the novel coronavirus disease (COVID-19). These measures included bans on large social gatherings; school closures; closures of entertainment venues, gyms, bars, and restaurant dining areas; and shelter-in-place orders. We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020, and April 27, 2020. An event study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate of confirmed COVID-19 cases by 5.4 percentage points after one to five days, 6.8 percentage points after six to ten days, 8.2 percentage points after eleven to fifteen days, and 9.1 percentage points after sixteen to twenty days. Holding the amount of voluntary social distancing constant, these results imply that there would have been ten times greater spread of COVID-19 by April 27 without shelter-in-place orders (ten million cases) and more than thirty-five times greater spread without any of the four measures (thirty-five million cases). Our article illustrates the potential danger of exponential spread in the absence of interventions, providing information relevant to strategies for restarting economic activity.
DOI: 10.1377/hlthaff.2020.00608
PubMed: 32407171
Affiliations:
Links toward previous steps (curation, corpus...)
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These measures included bans on large social gatherings; school closures; closures of entertainment venues, gyms, bars, and restaurant dining areas; and shelter-in-place orders. We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020, and April 27, 2020. An event study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate of confirmed COVID-19 cases by 5.4 percentage points after one to five days, 6.8 percentage points after six to ten days, 8.2 percentage points after eleven to fifteen days, and 9.1 percentage points after sixteen to twenty days. Holding the amount of voluntary social distancing constant, these results imply that there would have been ten times greater spread of COVID-19 by April 27 without shelter-in-place orders (ten million cases) and more than thirty-five times greater spread without any of the four measures (thirty-five million cases). Our article illustrates the potential danger of exponential spread in the absence of interventions, providing information relevant to strategies for restarting economic activity.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32407171</PMID><DateCompleted><Year>2020</Year><Month>07</Month><Day>21</Day></DateCompleted><DateRevised><Year>2020</Year><Month>12</Month><Day>10</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1544-5208</ISSN><JournalIssue CitedMedium="Internet"><Volume>39</Volume><Issue>7</Issue><PubDate><Year>2020</Year><Month>Jul</Month></PubDate></JournalIssue><Title>Health affairs (Project Hope)</Title><ISOAbbreviation>Health Aff (Millwood)</ISOAbbreviation></Journal><ArticleTitle>Strong Social Distancing Measures In The United States Reduced The COVID-19 Growth Rate.</ArticleTitle><Pagination><MedlinePgn>1237-1246</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1377/hlthaff.2020.00608</ELocationID><Abstract><AbstractText>State and local governments imposed social distancing measures in March and April 2020 to contain the spread of the novel coronavirus disease (COVID-19). These measures included bans on large social gatherings; school closures; closures of entertainment venues, gyms, bars, and restaurant dining areas; and shelter-in-place orders. We evaluated the impact of these measures on the growth rate of confirmed COVID-19 cases across US counties between March 1, 2020, and April 27, 2020. An event study design allowed each policy's impact on COVID-19 case growth to evolve over time. Adoption of government-imposed social distancing measures reduced the daily growth rate of confirmed COVID-19 cases by 5.4 percentage points after one to five days, 6.8 percentage points after six to ten days, 8.2 percentage points after eleven to fifteen days, and 9.1 percentage points after sixteen to twenty days. Holding the amount of voluntary social distancing constant, these results imply that there would have been ten times greater spread of COVID-19 by April 27 without shelter-in-place orders (ten million cases) and more than thirty-five times greater spread without any of the four measures (thirty-five million cases). Our article illustrates the potential danger of exponential spread in the absence of interventions, providing information relevant to strategies for restarting economic activity.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Courtemanche</LastName><ForeName>Charles</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Charles Courtemanche (courtemanche@uky.edu) is an associate professor of economics at the University of Kentucky, in Lexington, Kentucky.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Garuccio</LastName><ForeName>Joseph</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Joseph Garuccio is a doctoral student in economics at Georgia State University, in Atlanta, Georgia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Le</LastName><ForeName>Anh</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Anh Le is a doctoral student in economics at the University of Kentucky.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pinkston</LastName><ForeName>Joshua</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Joshua Pinkston is an associate professor of economics at the University of Louisville, in Louisville, Kentucky.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yelowitz</LastName><ForeName>Aaron</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Aaron Yelowitz is a professor of economics at the University of Kentucky.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>05</Month><Day>14</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Health Aff (Millwood)</MedlineTA><NlmUniqueID>8303128</NlmUniqueID><ISSNLinking>0278-2715</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003140" MajorTopicYN="N">Communicable Disease Control</DescriptorName><QualifierName UI="Q000458" MajorTopicYN="Y">organization & administration</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018352" 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Type="Geographic">United States</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Access to care</Keyword><Keyword MajorTopicYN="N">Children's health</Keyword><Keyword MajorTopicYN="N">Coronavirus</Keyword><Keyword MajorTopicYN="N">Covid-19</Keyword><Keyword MajorTopicYN="N">Diseases</Keyword><Keyword MajorTopicYN="N">Health Policy</Keyword><Keyword MajorTopicYN="N">Hospital closures</Keyword><Keyword MajorTopicYN="N">Pandemics</Keyword><Keyword MajorTopicYN="N">Shelter in place</Keyword><Keyword MajorTopicYN="N">Social distancing</Keyword><Keyword MajorTopicYN="N">Stay at home</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>5</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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last="Courtemanche">Charles Courtemanche</name></region><name sortKey="Pinkston, Joshua" sort="Pinkston, Joshua" uniqKey="Pinkston J" first="Joshua" last="Pinkston">Joshua Pinkston</name></country><country name="Géorgie (pays)"><noRegion><name sortKey="Garuccio, Joseph" sort="Garuccio, Joseph" uniqKey="Garuccio J" first="Joseph" last="Garuccio">Joseph Garuccio</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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