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Levels of SARS-CoV-2 population exposure are considerably higher than suggested by seroprevalence surveys

Abstract:
COVID-19; Children; MitigationCOVID-19; Nens; MitigacióCOVID-19; Niños; MitigaciónDuring the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mitigation policies for children have been a topic of considerable uncertainty and debate. Although some children have co-morbidities which increase their risk for severe coronavirus disease (COVID-19), and complications such as multisystem inflammatory syndrome and long COVID, most children only get mild COVID-19. On the other hand, consistent evidence shows that mass mitigation measures had enormous adverse impacts on children. A central question can thus be posed: What amount of mitigation should children bear, in response to a disease that is disproportionally affecting older people? In this review, we analyze the distinct child versus adult epidemiology, policies, mitigation trade-offs and outcomes in children in Western Europe. The highly heterogenous European policies applied to children compared to adults did not lead to significant measurable differences in outcomes. Remarkably, the relative epidemiological importance of transmission from school-age children to other age groups remains uncertain, with current evidence suggesting that schools often follow, rather than lead, community transmission. Important learning points for future pandemics are summarized
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1009436

Authors

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Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
ORCID:
0000-0001-9418-2527
More by this author
Role:
Author
ORCID:
0000-0002-8809-726X
More by this author
Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
ORCID:
0000-0002-6523-185X
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-6507-6597


More from this funder
Funder identifier:
10.13039/501100000923
Grant:
DP200100747
More from this funder
Funder identifier:
10.13039/100000865
Grant:
OPP1193472
More from this funder
Funder identifier:
10.13039/100007421


Publisher:
Public Library of Science
Journal:
PLoS Computational Biology More from this journal
Volume:
17
Issue:
9
Pages:
e1009436-e1009436
Publication date:
2021-09-20
DOI:
EISSN:
1553-7358
ISSN:
1553-734X


Language:
English
Keywords:
Pubs id:
1197709
Local pid:
pubs:1197709
Source identifiers:
W3199750387
Deposit date:
2026-03-26
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

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