Assessing the impacts of timing on the health benefits, cost-effectiveness and relative affordability of COVID-19 vaccination programmes in 27 African Countries

Background The COVID-19 vaccine supply shortage in 2021 constrained rollout efforts in Africa while populations experienced waves of epidemics. As supply picks up, a key question becomes if vaccination remains an impactful and cost-effective strategy given changes in the timing of implementation. Methods We assessed the impact of timing using an epidemiological and economic model. We fitted our mathematical epidemiological model to reported COVID-19 deaths in 27 African countries to estimate the existing immunity (resulting from infection) before substantial vaccine rollout. We then projected health outcomes for different programme start dates (2021-01-01 to 2021-12-01, n = 12) and roll-out rates (slow, medium, fast; 275, 826, and 2066 doses/ million population-day, respectively) for viral vector and mRNA vaccines. Rollout rates used were derived from observed uptake trajectories. We collected data on vaccine delivery costs by country income group. Lastly, we calculated incremental cost-effectiveness ratios and relative affordability. Findings Vaccination programmes with early start dates incur the most health benefits and are most cost-effective. While incurring the most health benefits, fast vaccine roll-outs are not always the most cost-effective. At a willingness-to-pay threshold of 0.5xGDP per capita, vaccine programmes starting in August 2021 using mRNA and viral vector vaccines were cost-effective in 6-10 and 17-18 of 27 countries, respectively. Interpretation African countries with large proportions of their populations unvaccinated by late 2021 may find vaccination programmes less cost-effective than they could have been earlier in 2021. Lower vaccine purchasing costs and/or the emergence of new variants may improve cost-effectiveness. Funding Bill and Melinda Gates Foundation, World Health Organization, National Institute of Health Research (UK), Health Data Research (UK) ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The contributions of YL, CABP, AMM, ST-R, EA, BSC (Uzochukwu), TD, EB, RME, FR, JN, MJ and AN are supported by the International Decision Support Initiative, which is funded by the Bill and Melinda Gates Foundation (OPP1202541).MJ has received funding from the European Union's Horizon 2020 research and innovation programme - project EpiPose (Grant agreement number 101003688); MJ and RME have received funding from the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Modelling and Health Economics at Imperial College and LSHTM in partnership with UKHSA. The European Commission is not responsible for any use that may be made of the information it contains. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or UKHSA. The contribution of RME is also supported by the Health Data Research UK (HDR UK) (grant: MR/S003975/1). The contributions of CABP is supported by the World Health Organization. YL has also received funding from the Bill and Melinda Gates Foundation via grant INV-003174. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes We used publicly available aggregate data in this study, cited in the reference list or the Supplemental Material. The CovidM modelling framework has been published previously and is available on the CMMID COVID-19 GitHub page. All code used and country-specific intermediate results are publicly available at [https://github.com/yangclaraliu/covid\_vac\_africa][1]. A CHEERS checklist (2022 version) is presented in Supplemental Table S12. [https://github.com/yangclaraliu/covid\_vac\_africa][1] [1]: https://github.com/yangclaraliu/covid_vac_africa