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Modelling optimal vaccination strategy for SARS-CoV-2 in the UK
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Moore, Sam, Hill, Edward M., Dyson, Louise, Tildesley, Michael J. and Keeling, Matt J. (2021) Modelling optimal vaccination strategy for SARS-CoV-2 in the UK. PLoS Computational Biology, 17 (5). e1008849. doi:10.1371/journal.pcbi.1008849 ISSN 1553-7358.
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WRAP-Modelling-optimal-vaccination-strategy-SARS-CoV-2-202.pdf - Published Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1877Kb) | Preview |
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WRAP-Modelling-optimal-vaccination-strategy-SARS-CoV-2-2021.pdf - Accepted Version - Requires a PDF viewer. Available under License Creative Commons Attribution 4.0. Download (1912Kb) | Preview |
Official URL: https://doi.org/10.1371/journal.pcbi.1008849
Abstract
The COVID-19 outbreak has highlighted our vulnerability to novel infections.
Faced with this threat and no effective treatment, in line with many other countries, the UK adopted enforced social distancing (lockdown) to reduce transmission—successfully reducing the reproductive number R below one. However, given the large pool of susceptible individuals that remain, complete relaxation of controls is likely to generate a substantial further outbreak. Vaccination remains the only foreseeable means of both containing the infection and returning to normal interactions and behaviour. Here, we consider the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses. We show that, for a range of assumptions on the action and efficacy of the vaccine, targeting older age groups first is optimal and may be sufficient to stem the epidemic if the vaccine prevents transmission as well as disease.
| Item Type: | Journal Article | ||||||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine R Medicine > RM Therapeutics. Pharmacology |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics | ||||||||||||
| Library of Congress Subject Headings (LCSH): | COVID-19 Pandemic, 2020- , COVID-19 Pandemic, 2020- -- Great Britain, COVID-19 (Disease), COVID-19 (Disease) -- Prevention, COVID-19 (Disease) -- Vaccination , COVID-19 (Disease) -- Prevention -- Mathematical models | ||||||||||||
| Journal or Publication Title: | PLoS Computational Biology | ||||||||||||
| Publisher: | Public Library of Science | ||||||||||||
| ISSN: | 1553-7358 | ||||||||||||
| Book Title: | Modelling optimal vaccination strategy for SARS-CoV-2 in the UK | ||||||||||||
| Official Date: | 2021 | ||||||||||||
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| Volume: | 17 | ||||||||||||
| Number: | 5 | ||||||||||||
| Article Number: | e1008849 | ||||||||||||
| DOI: | 10.1371/journal.pcbi.1008849 | ||||||||||||
| Status: | Peer Reviewed | ||||||||||||
| Publication Status: | Published | ||||||||||||
| Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
| Date of first compliant deposit: | 5 March 2021 | ||||||||||||
| Date of first compliant Open Access: | 5 March 2021 | ||||||||||||
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