Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions

Panovska-Griffiths, J., Swallow, B., Hinch, R., Cohen, J., Rosenfeld, K., Stuart, R. M., Ferretti, L., Di Lauro, F., Wymant, C., Izzo, A., Waites, W., Viner, R., Bonell, C., Fraser, C., Klein, D., Kerr, C. C., Bashton, Matthew, Smith, Darren, Nelson, Andrew, Young, Greg, McCann, Claire and The COVID-19 Genomics UK (COG-UK) Consortium, (2022) Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions. Philosophical Transactions of the Royal Society A: Mathematical Physical and Engineering Sciences, 380 (2233). p. 20210315. ISSN 1364-503X

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Official URL: https://doi.org/10.1098/rsta.2021.0315

Abstract

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and the agent-based model Covasim, in June 2021, to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. Using these estimates in Covasim (calibrated 1 September 2020 to 20 June 2021), in June 2021, we found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Item Type: Article
Additional Information: Matthew Bashton, Andrew Nelson, Clare McCann, Greg Young and Darren Smith are members of the COVID-19 Genomics UK consortium.
Uncontrolled Keywords: COVID-19, Humans, Models, Statistical, SARS-CoV-2/genetics, Systems Analysis
Subjects: A300 Clinical Medicine
B100 Anatomy, Physiology and Pathology
Department: Faculties > Health and Life Sciences > Applied Sciences
Depositing User: Rachel Branson
Date Deposited: 22 Feb 2023 10:50
Last Modified: 22 Feb 2023 11:00
URI: https://nrl.northumbria.ac.uk/id/eprint/51467

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