Affiliation:
1. Center for Communicable Disease Dynamics Harvard T.H. Chan School of Public Health Boston Massachusetts USA
2. Department of Global Health and Social Medicine Harvard Medical School Boston Massachusetts USA
3. Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann‐Ping Hsu College of Public Health Georgia Southern University Statesboro Georgia USA
4. KAVI‐Institute of Clinical Research University of Nairobi Nairobi Kenya
5. Center for Epidemiological Modelling and Analysis University of Nairobi Nairobi Kenya
6. Paul G Allen School for Global Animal Health Washington State University Pullman Washington USA
7. Department of Health Services, Kiambu County Ministry of Health Kenya Kiambu County Kenya
8. Countway Library Harvard School of Medicine Boston Massachusetts USA
Abstract
AbstractObjectiveMathematical 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.MethodsWe 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.ResultsThe 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.ConclusionsWhile 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.
Funder
Centers for Disease Control and Prevention
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