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Age-dependent effects in the transmission and control of COVID-19 epidemics

2020· article· en· 1 860 citations· W3034304416 sur OpenAlex· 10.1038/s41591-020-0962-9

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Résumé

The COVID-19 pandemic has shown a markedly low proportion of cases among children1–4. Age disparities in observed cases could be explained by children having lower susceptibility to infection, lower propensity to show clinical symptoms or both. We evaluate these possibilities by fitting an age-structured mathematical model to epidemic data from China, Italy, Japan, Singapore, Canada and South Korea. We estimate that susceptibility to infection in individuals under 20 years of age is approximately half that of adults aged over 20 years, and that clinical symptoms manifest in 21% (95% credible interval: 12–31%) of infections in 10- to 19-year-olds, rising to 69% (57–82%) of infections in people aged over 70 years. Accordingly, we find that interventions aimed at children might have a relatively small impact on reducing SARS-CoV-2 transmission, particularly if the transmissibility of subclinical infections is low. Our age-specific clinical fraction and susceptibility estimates have implications for the expected global burden of COVID-19, as a result of demographic differences across settings. In countries with younger population structures—such as many low-income countries—the expected per capita incidence of clinical cases would be lower than in countries with older population structures, although it is likely that comorbidities in low-income countries will also influence disease severity. Without effective control measures, regions with relatively older populations could see disproportionally more cases of COVID-19, particularly in the later stages of an unmitigated epidemic. A new epidemiological study shows reduced susceptibility to SARS-CoV-2 and decreased risk of developing severe symptoms in people aged younger than 20 years, suggesting that children have limited contribution to spread of COVID-19.

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La notice

Revue
Nature Medicine
Thématique
COVID-19 epidemiological studies
Domaine
Mathematics
Établissements canadiens
Organismes subventionnaires
Economic and Social Research CouncilNational Institutes of HealthResearch Councils UKMedical Research CouncilRoyal SocietyGovernment of the United KingdomDepartment of Health and Social CareWellcome TrustNational Institute for Health and Care ResearchBill and Melinda Gates Foundation
Mots-clés
DemographyMedicineEpidemiologySubclinical infectionPandemicTransmission (telecommunications)PopulationPsychological interventionCoronavirus disease 2019 (COVID-19)Per capitaIncidence (geometry)Environmental healthDiseaseInfectious disease (medical specialty)Internal medicine
Résumé présent dans OpenAlex
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