The Contribution of the Age Distribution of Cases to COVID-19 Case Fatality Across Countries : A Nine-Country Demographic Study.
Identifieur interne : 000236 ( Main/Exploration ); précédent : 000235; suivant : 000237The Contribution of the Age Distribution of Cases to COVID-19 Case Fatality Across Countries : A Nine-Country Demographic Study.
Auteurs : Nikkil Sudharsanan ; Oliver Didzun ; Till B Rnighausen ; Pascal Geldsetzer [États-Unis]Source :
- Annals of internal medicine [ 1539-3704 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Allemagne (épidémiologie), Chine (épidémiologie), Enfant (MeSH), Enfant d'âge préscolaire (MeSH), Espagne (épidémiologie), Facteurs de risque (MeSH), Facteurs âges (MeSH), France (épidémiologie), Humains (MeSH), Infections à coronavirus (mortalité), Italie (épidémiologie), Jeune adulte (MeSH), Nourrisson (MeSH), Nouveau-né (MeSH), Pandémies (MeSH), Pays-Bas (épidémiologie), Pneumopathie virale (mortalité), République de Corée (épidémiologie), Suisse (épidémiologie), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), États-Unis (épidémiologie), Études transversales (MeSH).
- MESH :
- mortalité : Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Allemagne, Chine, Espagne, France, Italie, Pays-Bas, République de Corée, Suisse, États-Unis.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Enfant d'âge préscolaire, Facteurs de risque, Facteurs âges, Humains, Jeune adulte, Nourrisson, Nouveau-né, Pandémies, Sujet âgé, Sujet âgé de 80 ans ou plus, Études transversales.
- Wicri :
- geographic : République populaire de Chine, France, Allemagne, Italie, Pays-Bas, Espagne, Suisse, États-Unis.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), COVID-19 (MeSH), Child (MeSH), Child, Preschool (MeSH), China (epidemiology), Coronavirus Infections (mortality), Cross-Sectional Studies (MeSH), France (epidemiology), Germany (epidemiology), Humans (MeSH), Infant (MeSH), Infant, Newborn (MeSH), Italy (epidemiology), Middle Aged (MeSH), Netherlands (epidemiology), Pandemics (MeSH), Pneumonia, Viral (mortality), Republic of Korea (epidemiology), Risk Factors (MeSH), Spain (epidemiology), Switzerland (epidemiology), United States (epidemiology), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : China, France, Germany, Italy, Netherlands, Republic of Korea, Spain, Switzerland, United States.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, COVID-19, Child, Child, Preschool, Cross-Sectional Studies, Humans, Infant, Infant, Newborn, Middle Aged, Pandemics, Risk Factors, Young Adult.
Abstract
BACKGROUND
There is wide variation in coronavirus disease 2019 (COVID-19) case-fatality rates (CFRs) across countries, leading to uncertainty about the true lethality of the disease. A large part of this variation may be due to the ages of individuals who are tested and identified.
OBJECTIVE
To measure the contribution of distortions from the age distributions of confirmed cases to CFRs within and across populations.
DESIGN
Cross-sectional demographic study using aggregate data on COVID-19 cases and deaths by age.
SETTING
Population-based data from China, France, Germany, Italy, the Netherlands, South Korea, Spain, Switzerland, and the United States.
PARTICIPANTS
All individuals with confirmed COVID-19, as reported by each country as of 19 April 2020 (
MEASUREMENTS
Age-specific COVID-19 CFRs and age-specific population shares by country.
RESULTS
The overall observed CFR varies widely, with the highest rates in Italy (9.3%) and the Netherlands (7.4%) and the lowest rates in South Korea (1.6%) and Germany (0.7%). Adjustment for the age distribution of cases explains 66% of the variation across countries, with a resulting age-standardized median CFR of 1.9%. Among a larger sample of 95 countries, the observed variation in COVID-19 CFRs is 13 times larger than what would be expected on the basis of just differences in the age composition of countries.
LIMITATION
The age-adjusted rates assume that, conditional on age, COVID-19 mortality among diagnosed cases is the same as that among undiagnosed cases and that individuals of all ages are equally susceptible to severe acute respiratory syndrome coronavirus 2 infection.
CONCLUSION
Selective testing and identification of older cases considerably warps estimates of the lethality of COVID-19 within populations and comparisons across countries. Removing age distortions and focusing on differences in age-adjusted case fatality will be essential for accurately comparing countries' performance in caring for patients with COVID-19 and for monitoring the epidemic over time.
PRIMARY FUNDING SOURCE
Alexander von Humboldt Foundation.
DOI: 10.7326/M20-2973
PubMed: 32698605
PubMed Central: PMC7397549
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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code="subField">T.B.).</wicri:noCountry></affiliation></author><author><name sortKey="Didzun, Oliver" sort="Didzun, Oliver" uniqKey="Didzun O" first="Oliver" last="Didzun">Oliver Didzun</name><affiliation><nlm:affiliation>Justus Liebig University Giessen, Giessen, Germany (O.D.).</nlm:affiliation><wicri:noCountry code="subField">Germany (O.D.).</wicri:noCountry></affiliation></author><author><name sortKey="B Rnighausen, Till" sort="B Rnighausen, Till" uniqKey="B Rnighausen T" first="Till" last="B Rnighausen">Till B Rnighausen</name><affiliation><nlm:affiliation>Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany (N.S., T.B.).</nlm:affiliation><wicri:noCountry code="subField">T.B.).</wicri:noCountry></affiliation></author><author><name sortKey="Geldsetzer, Pascal" sort="Geldsetzer, Pascal" uniqKey="Geldsetzer P" first="Pascal" last="Geldsetzer">Pascal Geldsetzer</name><affiliation wicri:level="4"><nlm:affiliation>Primary Care and Population Health, Stanford University, Stanford, California (P.G.).</nlm:affiliation><orgName type="university">Université Stanford</orgName><country>États-Unis</country><placeName><settlement type="city">Stanford (Californie)</settlement><region type="state">Californie</region></placeName></affiliation></author></analytic><series><title level="j">Annals of internal medicine</title><idno type="eISSN">1539-3704</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Age Factors (MeSH)</term><term>Aged (MeSH)</term><term>Aged, 80 and over (MeSH)</term><term>COVID-19 (MeSH)</term><term>Child (MeSH)</term><term>Child, Preschool (MeSH)</term><term>China (epidemiology)</term><term>Coronavirus Infections (mortality)</term><term>Cross-Sectional Studies (MeSH)</term><term>France (epidemiology)</term><term>Germany (epidemiology)</term><term>Humans (MeSH)</term><term>Infant (MeSH)</term><term>Infant, Newborn (MeSH)</term><term>Italy (epidemiology)</term><term>Middle Aged (MeSH)</term><term>Netherlands (epidemiology)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (mortality)</term><term>Republic of Korea (epidemiology)</term><term>Risk Factors (MeSH)</term><term>Spain (epidemiology)</term><term>Switzerland (epidemiology)</term><term>United States (epidemiology)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent (MeSH)</term><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Allemagne (épidémiologie)</term><term>Chine (épidémiologie)</term><term>Enfant (MeSH)</term><term>Enfant d'âge préscolaire (MeSH)</term><term>Espagne (épidémiologie)</term><term>Facteurs de risque (MeSH)</term><term>Facteurs âges (MeSH)</term><term>France (épidémiologie)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (mortalité)</term><term>Italie (épidémiologie)</term><term>Jeune adulte (MeSH)</term><term>Nourrisson (MeSH)</term><term>Nouveau-né (MeSH)</term><term>Pandémies (MeSH)</term><term>Pays-Bas (épidémiologie)</term><term>Pneumopathie virale (mortalité)</term><term>République de Corée (épidémiologie)</term><term>Suisse (épidémiologie)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term><term>États-Unis (épidémiologie)</term><term>Études transversales (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>China</term><term>France</term><term>Germany</term><term>Italy</term><term>Netherlands</term><term>Republic of Korea</term><term>Spain</term><term>Switzerland</term><term>United States</term></keywords><keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Allemagne</term><term>Chine</term><term>Espagne</term><term>France</term><term>Italie</term><term>Pays-Bas</term><term>République de Corée</term><term>Suisse</term><term>États-Unis</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Age Factors</term><term>Aged</term><term>Aged, 80 and over</term><term>COVID-19</term><term>Child</term><term>Child, Preschool</term><term>Cross-Sectional Studies</term><term>Humans</term><term>Infant</term><term>Infant, Newborn</term><term>Middle Aged</term><term>Pandemics</term><term>Risk Factors</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Facteurs de risque</term><term>Facteurs âges</term><term>Humains</term><term>Jeune adulte</term><term>Nourrisson</term><term>Nouveau-né</term><term>Pandémies</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term><term>Études transversales</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term><term>France</term><term>Allemagne</term><term>Italie</term><term>Pays-Bas</term><term>Espagne</term><term>Suisse</term><term>États-Unis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>There is wide variation in coronavirus disease 2019 (COVID-19) case-fatality rates (CFRs) across countries, leading to uncertainty about the true lethality of the disease. A large part of this variation may be due to the ages of individuals who are tested and identified.</p></div><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b></p><p>To measure the contribution of distortions from the age distributions of confirmed cases to CFRs within and across populations.</p></div><div type="abstract" xml:lang="en"><p><b>DESIGN</b></p><p>Cross-sectional demographic study using aggregate data on COVID-19 cases and deaths by age.</p></div><div type="abstract" xml:lang="en"><p><b>SETTING</b></p><p>Population-based data from China, France, Germany, Italy, the Netherlands, South Korea, Spain, Switzerland, and the United States.</p></div><div type="abstract" xml:lang="en"><p><b>PARTICIPANTS</b></p><p>All individuals with confirmed COVID-19, as reported by each country as of 19 April 2020 (</p></div><div type="abstract" xml:lang="en"><p><b>MEASUREMENTS</b></p><p>Age-specific COVID-19 CFRs and age-specific population shares by country.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>The overall observed CFR varies widely, with the highest rates in Italy (9.3%) and the Netherlands (7.4%) and the lowest rates in South Korea (1.6%) and Germany (0.7%). Adjustment for the age distribution of cases explains 66% of the variation across countries, with a resulting age-standardized median CFR of 1.9%. Among a larger sample of 95 countries, the observed variation in COVID-19 CFRs is 13 times larger than what would be expected on the basis of just differences in the age composition of countries.</p></div><div type="abstract" xml:lang="en"><p><b>LIMITATION</b></p><p>The age-adjusted rates assume that, conditional on age, COVID-19 mortality among diagnosed cases is the same as that among undiagnosed cases and that individuals of all ages are equally susceptible to severe acute respiratory syndrome coronavirus 2 infection.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>Selective testing and identification of older cases considerably warps estimates of the lethality of COVID-19 within populations and comparisons across countries. Removing age distortions and focusing on differences in age-adjusted case fatality will be essential for accurately comparing countries' performance in caring for patients with COVID-19 and for monitoring the epidemic over time.</p></div><div type="abstract" xml:lang="en"><p><b>PRIMARY FUNDING SOURCE</b></p><p>Alexander von Humboldt Foundation.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32698605</PMID><DateCompleted><Year>2020</Year><Month>11</Month><Day>13</Day></DateCompleted><DateRevised><Year>2021</Year><Month>01</Month><Day>10</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1539-3704</ISSN><JournalIssue CitedMedium="Internet"><Volume>173</Volume><Issue>9</Issue><PubDate><Year>2020</Year><Month>11</Month><Day>03</Day></PubDate></JournalIssue><Title>Annals of internal medicine</Title><ISOAbbreviation>Ann Intern Med</ISOAbbreviation></Journal><ArticleTitle>The Contribution of the Age Distribution of Cases to COVID-19 Case Fatality Across Countries : A Nine-Country Demographic Study.</ArticleTitle><Pagination><MedlinePgn>714-720</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.7326/M20-2973</ELocationID><Abstract><AbstractText Label="BACKGROUND">There is wide variation in coronavirus disease 2019 (COVID-19) case-fatality rates (CFRs) across countries, leading to uncertainty about the true lethality of the disease. A large part of this variation may be due to the ages of individuals who are tested and identified.</AbstractText><AbstractText Label="OBJECTIVE">To measure the contribution of distortions from the age distributions of confirmed cases to CFRs within and across populations.</AbstractText><AbstractText Label="DESIGN">Cross-sectional demographic study using aggregate data on COVID-19 cases and deaths by age.</AbstractText><AbstractText Label="SETTING">Population-based data from China, France, Germany, Italy, the Netherlands, South Korea, Spain, Switzerland, and the United States.</AbstractText><AbstractText Label="PARTICIPANTS">All individuals with confirmed COVID-19, as reported by each country as of 19 April 2020 (<i>n</i> = 1 223 261).</AbstractText><AbstractText Label="MEASUREMENTS">Age-specific COVID-19 CFRs and age-specific population shares by country.</AbstractText><AbstractText Label="RESULTS">The overall observed CFR varies widely, with the highest rates in Italy (9.3%) and the Netherlands (7.4%) and the lowest rates in South Korea (1.6%) and Germany (0.7%). Adjustment for the age distribution of cases explains 66% of the variation across countries, with a resulting age-standardized median CFR of 1.9%. Among a larger sample of 95 countries, the observed variation in COVID-19 CFRs is 13 times larger than what would be expected on the basis of just differences in the age composition of countries.</AbstractText><AbstractText Label="LIMITATION">The age-adjusted rates assume that, conditional on age, COVID-19 mortality among diagnosed cases is the same as that among undiagnosed cases and that individuals of all ages are equally susceptible to severe acute respiratory syndrome coronavirus 2 infection.</AbstractText><AbstractText Label="CONCLUSION">Selective testing and identification of older cases considerably warps estimates of the lethality of COVID-19 within populations and comparisons across countries. Removing age distortions and focusing on differences in age-adjusted case fatality will be essential for accurately comparing countries' performance in caring for patients with COVID-19 and for monitoring the epidemic over time.</AbstractText><AbstractText Label="PRIMARY FUNDING SOURCE">Alexander von Humboldt Foundation.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sudharsanan</LastName><ForeName>Nikkil</ForeName><Initials>N</Initials><Identifier Source="ORCID">0000-0003-1710-4634</Identifier><AffiliationInfo><Affiliation>Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany (N.S., T.B.).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Didzun</LastName><ForeName>Oliver</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>Justus Liebig University Giessen, Giessen, Germany (O.D.).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bärnighausen</LastName><ForeName>Till</ForeName><Initials>T</Initials><AffiliationInfo><Affiliation>Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany (N.S., T.B.).</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Geldsetzer</LastName><ForeName>Pascal</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Primary Care and Population Health, Stanford University, Stanford, California (P.G.).</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>22</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Ann Intern Med</MedlineTA><NlmUniqueID>0372351</NlmUniqueID><ISSNLinking>0003-4819</ISSNLinking></MedlineJournalInfo><CitationSubset>AIM</CitationSubset><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="CommentIn"><RefSource>Ann Intern Med. 2020 Nov 3;173(9):762-763</RefSource><PMID Version="1">32698604</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003430" MajorTopicYN="N">Cross-Sectional Studies</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005602" MajorTopicYN="N" Type="Geographic">France</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007223" MajorTopicYN="N">Infant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007231" MajorTopicYN="N">Infant, Newborn</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007558" MajorTopicYN="N" Type="Geographic">Italy</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009426" MajorTopicYN="N" Type="Geographic">Netherlands</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000401" MajorTopicYN="Y">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D056910" MajorTopicYN="N" Type="Geographic">Republic of Korea</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013030" MajorTopicYN="N" Type="Geographic">Spain</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013557" MajorTopicYN="N" Type="Geographic">Switzerland</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014481" MajorTopicYN="N" Type="Geographic">United States</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>7</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>18</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>7</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32698605</ArticleId><ArticleId IdType="doi">10.7326/M20-2973</ArticleId><ArticleId IdType="pmc">PMC7397549</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Ann Intern Med. 2020 Aug 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May;5(5):e256</Citation><ArticleIdList><ArticleId IdType="pubmed">32199471</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet. 2010 Nov 27;376(9755):1853-60</Citation><ArticleIdList><ArticleId IdType="pubmed">21075444</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet Public Health. 2020 May;5(5):e253</Citation><ArticleIdList><ArticleId IdType="pubmed">32220653</ArticleId></ArticleIdList></Reference></ReferenceList></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><noCountry><name sortKey="B Rnighausen, Till" sort="B Rnighausen, Till" uniqKey="B Rnighausen T" first="Till" last="B Rnighausen">Till B Rnighausen</name><name sortKey="Didzun, Oliver" sort="Didzun, Oliver" uniqKey="Didzun O" first="Oliver" last="Didzun">Oliver Didzun</name><name sortKey="Sudharsanan, Nikkil" sort="Sudharsanan, Nikkil" uniqKey="Sudharsanan N" first="Nikkil" last="Sudharsanan">Nikkil Sudharsanan</name></noCountry><country name="États-Unis"><region name="Californie"><name sortKey="Geldsetzer, Pascal" sort="Geldsetzer, Pascal" uniqKey="Geldsetzer P" first="Pascal" last="Geldsetzer">Pascal Geldsetzer</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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