Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review
Abstract 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, trans...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-12-01
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| Series: | BMC Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12916-021-02190-3 |
| _version_ | 1830179523224666112 |
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| author | Nuru Saadi Y-Ling Chi Srobana Ghosh Rosalind M. Eggo Ciara V. McCarthy Matthew Quaife Jeanette Dawa Mark Jit Anna Vassall |
| author_facet | Nuru Saadi Y-Ling Chi Srobana Ghosh Rosalind M. Eggo Ciara V. McCarthy Matthew Quaife Jeanette Dawa Mark Jit Anna Vassall |
| author_sort | Nuru Saadi |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-17T20:00:45Z |
| format | Article |
| id | doaj.art-37345c643f8b4c038ab387eb799316e3 |
| institution | Directory Open Access Journal |
| issn | 1741-7015 |
| language | English |
| last_indexed | 2024-12-17T20:00:45Z |
| publishDate | 2021-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medicine |
| spelling | doaj.art-37345c643f8b4c038ab387eb799316e32022-12-21T21:34:29ZengBMCBMC Medicine1741-70152021-12-0119111110.1186/s12916-021-02190-3Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative reviewNuru Saadi0Y-Ling Chi1Srobana Ghosh2Rosalind M. Eggo3Ciara V. McCarthy4Matthew Quaife5Jeanette Dawa6Mark Jit7Anna Vassall8Department of Global Health and Development, London School of Hygiene and Tropical MedicineInternational Decision Support Initiative, Center for Global DevelopmentInternational Decision Support Initiative, Center for Global DevelopmentCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical MedicineCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical MedicineCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical MedicineWashington State University - Global Health ProgramCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical MedicineDepartment of Global Health and Development, London School of Hygiene and Tropical MedicineAbstract 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.https://doi.org/10.1186/s12916-021-02190-3COVID-19, Vaccination, Mathematical modelling |
| spellingShingle | Nuru Saadi Y-Ling Chi Srobana Ghosh Rosalind M. Eggo Ciara V. McCarthy Matthew Quaife Jeanette Dawa Mark Jit Anna Vassall Models of COVID-19 vaccine prioritisation: a systematic literature search and narrative review BMC Medicine COVID-19, Vaccination, Mathematical modelling |
| 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 | COVID-19, Vaccination, Mathematical modelling |
| url | https://doi.org/10.1186/s12916-021-02190-3 |
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