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

J. Panovska-Griffiths; B. Swallow; R. Hinch; J. Cohen; K. Rosenfeld; R. M. Stuart; L. Ferretti; F. Di Lauro; C. Wymant; A. Izzo; W. Waites; R. Viner; C. Bonell; C. Fraser; D. Klein; C. C. Kerr; The COVID-19 Genomics UK (COG-UK) Consortium

doi:10.1098/rsta.2021.0315

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

J. Panovska-Griffiths^*, B. Swallow, R. Hinch, J. Cohen, K. Rosenfeld, R. M. Stuart, L. Ferretti, F. Di Lauro, C. Wymant, A. Izzo, W. Waites, R. Viner, C. Bonell, C. Fraser, D. Klein, C. C. Kerr, The COVID-19 Genomics UK (COG-UK) Consortium

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Article number	20210315
Number of pages	19
Journal	Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume	380
Issue number	2233
Early online date	15 Aug 2022
DOIs	https://doi.org/10.1098/rsta.2021.0315
Publication status	Published - 3 Oct 2022

Keywords

Multivariateregression modelling
COVID-19
Agent-based modelling

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Panovska-Griffiths_2022_RSPTA_Statistical-agent-based_CC
Copyright © 2022 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
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Cite this

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., & 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), Article 20210315. https://doi.org/10.1098/rsta.2021.0315

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

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.",

keywords = "Multivariateregression modelling, COVID-19, Agent-based modelling",

author = "J. Panovska-Griffiths and B. Swallow and R. Hinch and J. Cohen and K. Rosenfeld and Stuart, {R. M.} and L. Ferretti and {Di Lauro}, F. and C. Wymant and A. Izzo and W. Waites and R. Viner and C. Bonell and C. Fraser and D. Klein and Kerr, {C. C.} and {The COVID-19 Genomics UK (COG-UK) Consortium}",

note = "J.P.G.{\textquoteright}s work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care (DHSC). This work was also supported by DHSC funding awarded to C.F. and Li Ka Shing Foundation grant awarded to C.F. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) (grant code: MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute.",

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Panovska-Griffiths, J, Swallow, B, Hinch, R, Cohen, J, Rosenfeld, K, Stuart, RM, Ferretti, L, Di Lauro, F, Wymant, C, Izzo, A, Waites, W, Viner, R, Bonell, C, Fraser, C, Klein, D, Kerr, CC & 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, vol. 380, no. 2233, 20210315. https://doi.org/10.1098/rsta.2021.0315

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. et al.
In: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 380, No. 2233, 20210315, 03.10.2022.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions

AU - Panovska-Griffiths, J.

AU - Swallow, B.

AU - Hinch, R.

AU - Cohen, J.

AU - Rosenfeld, K.

AU - Stuart, R. M.

AU - Ferretti, L.

AU - Di Lauro, F.

AU - Wymant, C.

AU - Izzo, A.

AU - Waites, W.

AU - Viner, R.

AU - Bonell, C.

AU - Fraser, C.

AU - Klein, D.

AU - Kerr, C. C.

AU - The COVID-19 Genomics UK (COG-UK) Consortium

N1 - J.P.G.’s work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care (DHSC). This work was also supported by DHSC funding awarded to C.F. and Li Ka Shing Foundation grant awarded to C.F. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) (grant code: MC_PC_19027), and Genome Research Limited, operating as the Wellcome Sanger Institute.

PY - 2022/10/3

Y1 - 2022/10/3

N2 - 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.

AB - 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.

KW - Multivariateregression modelling

KW - COVID-19

KW - Agent-based modelling

U2 - 10.1098/rsta.2021.0315

DO - 10.1098/rsta.2021.0315

M3 - Article

SN - 1364-503X

VL - 380

JO - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

JF - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

IS - 2233

M1 - 20210315

ER -

Panovska-Griffiths J, Swallow B, Hinch R, Cohen J, Rosenfeld K, Stuart RM et al. 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. 2022 Oct 3;380(2233):20210315. Epub 2022 Aug 15. doi: 10.1098/rsta.2021.0315

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

Abstract

Keywords

UN SDGs

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