COVID‐19 vaccination strategies in Africa: A scoping review of the use of mathematical models to inform policy
Objective Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID‐19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID‐19 vaccinatio...
Saved in:
Published in | Tropical medicine & international health Vol. 29; no. 6; pp. 466 - 476 |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.06.2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Objective
Mathematical models are vital tools to understand transmission dynamics and assess the impact of interventions to mitigate COVID‐19. However, historically, their use in Africa has been limited. In this scoping review, we assess how mathematical models were used to study COVID‐19 vaccination to potentially inform pandemic planning and response in Africa.
Methods
We searched six electronic databases: MEDLINE, Embase, Web of Science, Global Health, MathSciNet and Africa‐Wide NiPAD, using keywords to identify articles focused on the use of mathematical modelling studies of COVID‐19 vaccination in Africa that were published as of October 2022. We extracted the details on the country, author affiliation, characteristics of models, policy intent and heterogeneity factors. We assessed quality using 21‐point scale criteria on model characteristics and content of the studies.
Results
The literature search yielded 462 articles, of which 32 were included based on the eligibility criteria. Nineteen (59%) studies had a first author affiliated with an African country. Of the 32 included studies, 30 (94%) were compartmental models. By country, most studies were about or included South Africa (n = 12, 37%), followed by Morocco (n = 6, 19%) and Ethiopia (n = 5, 16%). Most studies (n = 19, 59%) assessed the impact of increasing vaccination coverage on COVID‐19 burden. Half (n = 16, 50%) had policy intent: prioritising or selecting interventions, pandemic planning and response, vaccine distribution and optimisation strategies and understanding transmission dynamics of COVID‐19. Fourteen studies (44%) were of medium quality and eight (25%) were of high quality.
Conclusions
While decision‐makers could draw vital insights from the evidence generated from mathematical modelling to inform policy, we found that there was limited use of such models exploring vaccination impacts for COVID‐19 in Africa. The disparity can be addressed by scaling up mathematical modelling training, increasing collaborative opportunities between modellers and policymakers, and increasing access to funding. |
---|---|
Bibliography: | Sustainable Development Goals (Goal 3) Good Health and Wellbeing The findings, conclusions and views expressed are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention (CDC). The CDC played no role in the design or conduct of the study. ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 |
ISSN: | 1360-2276 1365-3156 |
DOI: | 10.1111/tmi.13994 |