Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: A mathematical modelling analysis

Alexandra B. Hogan*, Peter Winskill, Oliver J. Watson, Patrick G.T. Walker, Charles Whittaker, Marc Baguelin, Nicholas F. Brazeau, Giovanni D. Charles, Katy A.M. Gaythorpe, Arran Hamlet, Edward Knock, Daniel J. Laydon, John A. Lees, Alessandra Løchen, Robert Verity, Lilith K. Whittles, Farzana Muhib, Katharina Hauck, Neil M. Ferguson, Azra C. Ghani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The worldwide endeavour to develop safe and effective COVID-19 vaccines has been extraordinary, and vaccination is now underway in many countries. However, the doses available in 2021 are likely to be limited. We extend a mathematical model of SARS-CoV-2 transmission across different country settings to evaluate the public health impact of potential vaccines using WHO-developed target product profiles. We identify optimal vaccine allocation strategies within- and between-countries to maximise averted deaths under constraints on dose supply. We find that the health impact of SARS-CoV-2 vaccination depends on the cumulative population-level infection incidence when vaccination begins, the duration of natural immunity, the trajectory of the epidemic prior to vaccination, and the level of healthcare available to effectively treat those with disease. Within a country we find that for a limited supply (doses for < 20% of the population) the optimal strategy is to target the elderly. However, with a larger supply, if vaccination can occur while other interventions are maintained, the optimal strategy switches to targeting key transmitters to indirectly protect the vulnerable. As supply increases, vaccines that reduce or block infection have a greater impact than those that prevent disease alone due to the indirect protection provided to high-risk groups. Given a 2 billion global dose supply in 2021, we find that a strategy in which doses are allocated to countries proportional to population size is close to optimal in averting deaths and aligns with the ethical principles agreed in pandemic preparedness planning.

Original languageEnglish
Pages (from-to)2995-3006
Number of pages12
JournalVaccine
Volume39
Issue number22
DOIs
Publication statusPublished - 21 May 2021
Externally publishedYes

Bibliographical note

Funding Information:
The authors declare grants from The Wellcome Trust (NMF, ACG), UK Medical Research Council (NMF, ACG, KH), National Institute for Health Research (NMF, KH), Community Jameel (NMF, KH), the UK Foreign, Commonwealth and Development Office (OJW) and the Bill and Melinda Gates Foundation (NMF), during the conduct of the study; grants from the Bill and Melinda Gates Foundation (ACG), National Institute for Health (ACG), GlaxoSmithKline (AL), and Gavi, the Vaccine Alliance (ACG, KAMG) outside the submitted work; personal fees from the World Health Organization (ACG, ABH, MB, PW) during the conduct of the study, in relation to developing the online interface (approximately £1000 per individual); and personal fees from The Global Fund (ACG, PW) outside the submitted work. ABH was previously engaged by Pfizer Inc to advise on modelling RSV vaccination strategies for which she received no financial compensation. There are no other relationships or activities that could appear to have influenced the submitted work.

Funding Information:
PW and ABH acknowledge fellowship funding from Imperial College London. PGTW, OJW, ACG and NMF acknowledge grant funding from The Wellcome Trust and the UK Foreign, Commonwealth & Development Office (FCDO) (reference 221350/Z/20/Z). CW acknowledges support through a Medical Research Council (MRC) Doctoral Training Programme studentship. NB, GC and ACG acknowledge support from the Bill and Melinda Gates Foundation. All authors acknowledge funding support for the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK MRC and the UK FCDO, under the MRC/FCDO Concordat agreement, also part of the EDCTP2 programme supported by the European Union. NMF and KH acknowledge funding by Community Jameel. NMF acknowledges support from the NIHR HPRU in Modelling and Health Economics, a partnership between PHE, Imperial College London and LSHTM (grant code NIHR200908). DJL and NMF acknowledge funding from Vaccine Efficacy Evaluation for Priority Emerging Diseases (VEEPED) grant (reference NIHR: PR-OD-1017-20002) from the National Institute for Health Research. ACG, ABH, MB, and PW received personal fees from the World Health Organization in relation to developing the online interface (approximately GBP 1,000 per individual), and the WHO provided input into the design of and data underpinning the online interface. The funders had no other role in study design, conduct, or interpretation of results. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Disclaimer: The views expressed are those of the authors and not necessarily those of the United Kingdom (UK) Department of Health and Social Care, the National Health Service, the National Institute for Health Research (NIHR), or Public Health England (PHE).

Publisher Copyright:
© 2021 The Authors

Keywords

  • COVID-19
  • Mathematical model
  • Optimisation
  • SARS-CoV-2
  • Vaccination model

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