Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review.


Journal

BMC medicine
ISSN: 1741-7015
Titre abrégé: BMC Med
Pays: England
ID NLM: 101190723

Informations de publication

Date de publication:
01 12 2021
Historique:
received: 09 08 2021
accepted: 17 11 2021
entrez: 1 12 2021
pubmed: 2 12 2021
medline: 15 12 2021
Statut: epublish

Résumé

How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes. We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed. The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage. The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.

Sections du résumé

BACKGROUND
How best to prioritise COVID-19 vaccination within and between countries has been a public health and an ethical challenge for decision-makers globally. We reviewed epidemiological and economic modelling evidence on population priority groups to minimise COVID-19 mortality, transmission, and morbidity outcomes.
METHODS
We searched the National Institute of Health iSearch COVID-19 Portfolio (a database of peer-reviewed and pre-print articles), Econlit, the Centre for Economic Policy Research, and the National Bureau of Economic Research for mathematical modelling studies evaluating the impact of prioritising COVID-19 vaccination to population target groups. The first search was conducted on March 3, 2021, and an updated search on the LMIC literature was conducted from March 3, 2021, to September 24, 2021. We narratively synthesised the main study conclusions on prioritisation and the conditions under which the conclusions changed.
RESULTS
The initial search identified 1820 studies and 36 studies met the inclusion criteria. The updated search on LMIC literature identified 7 more studies. 43 studies in total were narratively synthesised. 74% of studies described outcomes in high-income countries (single and multi-country). We found that for countries seeking to minimise deaths, prioritising vaccination of senior adults was the optimal strategy and for countries seeking to minimise cases the young were prioritised. There were several exceptions to the main conclusion, notably that reductions in deaths could be increased if groups at high risk of both transmission and death could be further identified. Findings were also sensitive to the level of vaccine coverage.
CONCLUSION
The evidence supports WHO SAGE recommendations on COVID-19 vaccine prioritisation. There is, however, an evidence gap on optimal prioritisation for low- and middle-income countries, studies that included an economic evaluation, and studies that explore prioritisation strategies if the aim is to reduce overall health burden including morbidity.

Identifiants

pubmed: 34847950
doi: 10.1186/s12916-021-02190-3
pii: 10.1186/s12916-021-02190-3
pmc: PMC8632563
doi:

Substances chimiques

COVID-19 Vaccines 0

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

318

Subventions

Organisme : Medical Research Council
ID : MC_PC 19065
Pays : United Kingdom
Organisme : Bill & Melinda Gates Foundation
ID : INV-003174
Pays : United States

Informations de copyright

© 2021. The Author(s).

Références

BMJ. 2009 Jul 21;339:b2700
pubmed: 19622552
Proc Natl Acad Sci U S A. 2021 Apr 20;118(16):
pubmed: 33811185
BMJ Innov. 2021 Apr;7(2):327-336
pubmed: 34192020
Int J Infect Dis. 2021 Feb;103:431-438
pubmed: 33388436
J Clin Med. 2021 Feb 04;10(4):
pubmed: 33557344
Vaccine. 2021 Aug 16;39(35):5055-5063
pubmed: 34274126
BMJ Open. 2021 Jul 2;11(7):e048874
pubmed: 34215611
Virus Evol. 2022 Mar 17;8(1):veac002
pubmed: 35310621
Econ Lett. 2023 Mar;224:111008
pubmed: 36741504
Lancet. 2021 Mar 13;397(10278):1023-1034
pubmed: 33587887
Lancet Infect Dis. 2021 Aug;21(8):1097-1106
pubmed: 33811817
Vaccines (Basel). 2021 May 06;9(5):
pubmed: 34066317
Vaccine. 2022 Apr 14;40(17):2506-2513
pubmed: 33958223
PLoS Comput Biol. 2021 May 6;17(5):e1008849
pubmed: 33956791
Infect Dis Model. 2021;6:751-765
pubmed: 34127952
BMC Med. 2021 Jul 13;19(1):162
pubmed: 34253200
Science. 2021 Feb 26;371(6532):916-921
pubmed: 33479118
Pharmacoeconomics. 2021 Sep;39(9):1059-1073
pubmed: 34138458
Sci Adv. 2021 Feb 3;7(6):
pubmed: 33536223
PLoS Comput Biol. 2021 Sep 10;17(9):e1009346
pubmed: 34506478

Auteurs

Nuru Saadi (N)

Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK. Nuru.Saadi@lshtm.ac.uk.

Y-Ling Chi (YL)

International Decision Support Initiative, Center for Global Development, London, UK.

Srobana Ghosh (S)

International Decision Support Initiative, Center for Global Development, London, UK.

Rosalind M Eggo (RM)

Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Ciara V McCarthy (CV)

Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Matthew Quaife (M)

Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Jeanette Dawa (J)

Washington State University - Global Health Program, Nairobi, Kenya.
Center for Epidemiological Modelling and Analysis, University of Nairobi, Nairobi, Kenya.

Mark Jit (M)

Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.

Anna Vassall (A)

Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK.

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