A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2.


Journal

Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511

Informations de publication

Date de publication:
14 08 2020
Historique:
received: 07 05 2020
accepted: 18 06 2020
pubmed: 25 6 2020
medline: 28 8 2020
entrez: 25 6 2020
Statut: ppublish

Résumé

Despite various levels of preventive measures, in 2020, many countries have suffered severely from the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Using a model, we show that population heterogeneity can affect disease-induced immunity considerably because the proportion of infected individuals in groups with the highest contact rates is greater than that in groups with low contact rates. We estimate that if

Identifiants

pubmed: 32576668
pii: science.abc6810
doi: 10.1126/science.abc6810
pmc: PMC7331793
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

846-849

Informations de copyright

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Références

Proc Biol Sci. 2006 Nov 7;273(1602):2743-8
pubmed: 17015324
Science. 2020 Jun 26;368(6498):
pubmed: 32586992
Math Biosci. 2004 Sep;191(1):19-40
pubmed: 15312742
Phys Rev Lett. 2001 Apr 2;86(14):3200-3
pubmed: 11290142
Am J Epidemiol. 2006 Nov 15;164(10):936-44
pubmed: 16968863

Auteurs

Tom Britton (T)

Department of Mathematics, Stockholm University, Stockholm, Sweden. tom.britton@math.su.se.

Frank Ball (F)

School of Mathematical Sciences, University of Nottingham, Nottingham, UK.

Pieter Trapman (P)

Department of Mathematics, Stockholm University, Stockholm, Sweden.

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Classifications MeSH