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Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review
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,...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8632563/ https://www.ncbi.nlm.nih.gov/pubmed/34847950 http://dx.doi.org/10.1186/s12916-021-02190-3 |
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author | Saadi, Nuru Chi, Y-Ling Ghosh, Srobana Eggo, Rosalind M. McCarthy, Ciara V. Quaife, Matthew Dawa, Jeanette Jit, Mark Vassall, Anna |
author_facet | Saadi, Nuru Chi, Y-Ling Ghosh, Srobana Eggo, Rosalind M. McCarthy, Ciara V. Quaife, Matthew Dawa, Jeanette Jit, Mark Vassall, Anna |
author_sort | Saadi, Nuru |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-02190-3. |
format | Online Article Text |
id | pubmed-8632563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86325632021-12-01 Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review Saadi, Nuru Chi, Y-Ling Ghosh, Srobana Eggo, Rosalind M. McCarthy, Ciara V. Quaife, Matthew Dawa, Jeanette Jit, Mark Vassall, Anna BMC Med Review 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-021-02190-3. BioMed Central 2021-12-01 /pmc/articles/PMC8632563/ /pubmed/34847950 http://dx.doi.org/10.1186/s12916-021-02190-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Saadi, Nuru Chi, Y-Ling Ghosh, Srobana Eggo, Rosalind M. McCarthy, Ciara V. Quaife, Matthew Dawa, Jeanette Jit, Mark Vassall, Anna Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title | Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title_full | Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title_fullStr | Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title_full_unstemmed | Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title_short | Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review |
title_sort | models of covid-19 vaccine prioritisation: a systematic literature search and narrative review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8632563/ https://www.ncbi.nlm.nih.gov/pubmed/34847950 http://dx.doi.org/10.1186/s12916-021-02190-3 |
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