The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation

Centre for the Mathematical Modelling of Infectious Diseases COVID-19 working group, Frank Sandmann*, Nicholas G. Davies, Anna Vassall, William Edmunds, Mark Jit

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)
4 Downloads (Pure)

Abstract

Background: In response to the COVID-19 pandemic, the UK first adopted physical distancing measures in March, 2020. Vaccines against SARS-CoV-2 became available in December, 2020. We explored the health and economic value of introducing SARS-CoV-2 immunisation alongside physical distancing in the UK to gain insights about possible future scenarios in a post-vaccination era.

Methods: We used an age-structured dynamic transmission and economic model to explore different scenarios of UK mass immunisation programmes over 10 years. We compared vaccinating 75% of individuals aged 15 years or older (and annually revaccinating 50% of individuals aged 15–64 years and 75% of individuals aged 65 years or older) to no vaccination. We assumed either 50% vaccine efficacy against disease and 45-week protection (worst-case scenario) or 95% vaccine efficacy against infection and 3-year protection (best-case scenario). Natural immunity was assumed to wane within 45 weeks. We also explored the additional impact of physical distancing on vaccination by assuming either an initial lockdown followed by voluntary physical distancing, or an initial lockdown followed by increased physical distancing mandated above a certain threshold of incident daily infections. We considered benefits in terms of quality-adjusted life-years (QALYs) and costs, both to the health-care payer and the national economy. We discounted future costs and QALYs at 3·5% annually and assumed a monetary value per QALY of £20 000 and a conservative long-run cost per vaccine dose of £15. We explored and varied these parameters in sensitivity analyses. We expressed the health and economic benefits of each scenario with the net monetary value: QALYs × (monetary value per QALY) – costs.

Findings: Without the initial lockdown, vaccination, and increased physical distancing, we estimated 148·0 million (95% uncertainty interval 48·5–198·8) COVID-19 cases and 3·1 million (0·84–4·5) deaths would occur in the UK over 10 years. In the best-case scenario, vaccination minimises community transmission without future periods of increased physical distancing, whereas SARS-CoV-2 becomes endemic with biannual epidemics in the worst-case scenario. Ongoing transmission is also expected in intermediate scenarios with vaccine efficacy similar to published clinical trial data. From a health-care perspective, introducing vaccination leads to incremental net monetary values ranging from £12·0 billion to £334·7 billion in the best-case scenario and from –£1·1 billion to £56·9 billion in the worst-case scenario. Incremental net monetary values of increased physical distancing might be negative from a societal perspective if national economy losses are persistent and large.

Interpretation: Our model findings highlight the substantial health and economic value of introducing SARS-CoV-2 vaccination. Smaller outbreaks could continue even with vaccines, but population-wide implementation of increased physical distancing might no longer be justifiable. Our study provides early insights about possible future post-vaccination scenarios from an economic and epidemiological perspective.

Funding: National Institute for Health Research, European Commission, Bill & Melinda Gates Foundation.

Original languageEnglish
Pages (from-to)962-974
Number of pages13
JournalThe Lancet Infectious Diseases
Volume21
Issue number7
Early online date18 Mar 2021
DOIs
Publication statusPublished - 1 Jul 2021

Bibliographical note

Funding Information:
This research was partly funded by the Bill & Melinda Gates Foundation (INV-003174: MJ). This project has received funding from the European Union's Horizon 2020 research and innovation programme, project EpiPose (101003688: MJ and WJE). This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. FGS, NGD, AV, WJE, and MJ were supported by the NIHR Health Protection Research Unit (HPRU) in Modelling and Health Economics, a partnership between Public Health England (PHE), Imperial College London, and the London School of Hygiene & Tropical Medicine (LSHTM; grant code NIHR200908). MJ and ND were supported by the NIHR HPRU in Immunisation at LSHTM in partnership with PHE (grant reference code NIHR200929). WJE was supported by the NIHR programme Vaccine Efficacy Evaluation for Priority Emerging Diseases (grant code PR-OD-1017-20002). The views expressed in this publication are those of the authors and not necessarily those of the European Commission, NIHR, PHE, or the UK Department of Health and Social Care. The funding sources for the working group authors are as follows: Alan Turing Institute (Akira Endo), Biotechnology and Biological Sciences Research Council London Interdisciplinary Doctoral Program studentship (BB/M009513/1: David Simons), Bill & Melinda Gates Foundation (INV-001754: Matthew Quaife; INV-003174: Kiesha Prem and Yang Liu; NTD Modelling Consortium OPP1184344: Carl A B Pearson and Graham F Medley; OPP1180644: Simon R Procter; OPP1183986: Emily S Nightingale; OPP1191821: Megan Auzenbergs; and OPP1157270: Kaja Abbas), Department for International Development (DFID)/Wellcome Trust (Epidemic Preparedness Coronavirus research programme 221303/Z/20/Z: Carl A B Pearson and Kevin van Zandvoort), Elrha R2HC/UK DFID/Wellcome Trust (Kevin van Zandvoort), ERC Starting Grant (#757699: Matthew Quaife), EpiPose (101003688: Kiesha Prem, Petra Klepac, Rosanna C Barnard, and Yang Liu), Global Challenges Research Fund project RECAP managed through Research Councils UK and the Economic and Social Research Council (ES/P010873/1: Amy Gimma, Christopher I Jarvis, and Thibaut Jombart), Health Data Research UK (MR/S003975/1: Rosalind M Eggo), Medical Research Council (MR/N013638/1: Naomi R Waterlow; LID DTP MR/N013638/1: Georgia R Gore-Langton; MC_PC_19065: Amy Gimma, Rosalind M Eggo, Samuel Clifford, Thibaut Jombart, and Yang Liu; and MR/P014658/1: Gwenan M Knight), Nakajima Foundation (Akira Endo), NIHR (16/136/46 and 16/137/109: Billy J Quilty, Charlie Diamond, Fiona Yueqian Sun, and Yang Liu; HPRU for Modelling Methodology HPRU-2012-10096: Thibaut Jombart; PR-OD-1017-20002: Alicia Rosello), Royal Society (Dorothy Hodgkin Fellowship: Rachel Lowe; RP\EA\180004: Petra Klepac), UK Department of Health and Social Care/UK Aid/NIHR (ITCRZ 03010: HPG), UK Public Health Rapid Support Team funded by the UK Department of Health and Social Care (Thibaut Jombart), and the Wellcome Trust (206250/Z/17/Z: Adam J Kucharski and Timothy W Russell, 206471/Z/17/Z: Oliver J Brady; 208812/Z/17/Z: Samuel Clifford and Stefan Flasche; 210758/Z/18/Z: James D Munday, Joel Hellewell, Katharine Sherratt, Nikos I Bosse, Sam Abbott, Sebastian Funk, and Sophie R Meakin).
NGD, MJ, and WJE are participants of the Scientific Pandemic Influenza Group on Modelling. WJE is a participant of the Scientific Advisory Group for Emergencies. All authors declare no competing interests.

Open Access: This is an Open Access article under the CC BY 4.0 license.

Publisher Copyright: © 2021 The Author(s). Published by Elsevier Ltd.

Citation: Sandmann, Frank G., et al. "The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation." The Lancet Infectious Diseases (2021).

DOI: https://doi.org/10.1016/S1473-3099(21)00079-7

Fingerprint

Dive into the research topics of 'The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation'. Together they form a unique fingerprint.

Cite this