Model-informed COVID-19 vaccine prioritization strategies by age and serostatus.


Journal

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

Informations de publication

Date de publication:
26 02 2021
Historique:
received: 08 09 2020
accepted: 12 01 2021
pubmed: 23 1 2021
medline: 6 3 2021
entrez: 22 1 2021
Statut: ppublish

Résumé

Limited initial supply of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine raises the question of how to prioritize available doses. We used a mathematical model to compare five age-stratified prioritization strategies. A highly effective transmission-blocking vaccine prioritized to adults ages 20 to 49 years minimized cumulative incidence, but mortality and years of life lost were minimized in most scenarios when the vaccine was prioritized to adults greater than 60 years old. Use of individual-level serological tests to redirect doses to seronegative individuals improved the marginal impact of each dose while potentially reducing existing inequities in COVID-19 impact. Although maximum impact prioritization strategies were broadly consistent across countries, transmission rates, vaccination rollout speeds, and estimates of naturally acquired immunity, this framework can be used to compare impacts of prioritization strategies across contexts.

Identifiants

pubmed: 33479118
pii: science.abe6959
doi: 10.1126/science.abe6959
pmc: PMC7963218
doi:

Substances chimiques

Antibodies, Viral 0
COVID-19 Vaccines 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

916-921

Subventions

Organisme : NCI NIH HHS
ID : U01 CA261277
Pays : United States

Commentaires et corrections

Type : UpdateOf
Type : CommentIn

Informations de copyright

Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Auteurs

Kate M Bubar (KM)

Department of Applied Mathematics, University of Colorado Boulder, Boulder, CO 80309, USA. kate.bubar@colorado.edu daniel.larremore@colorado.edu.
IQ Biology Program, University of Colorado Boulder, Boulder, CO 80303, USA.

Kyle Reinholt (K)

Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA.

Stephen M Kissler (SM)

Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.

Marc Lipsitch (M)

Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.
Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.

Sarah Cobey (S)

Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.

Yonatan H Grad (YH)

Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA.

Daniel B Larremore (DB)

Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA. kate.bubar@colorado.edu daniel.larremore@colorado.edu.
BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, USA.

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Classifications MeSH