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Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions
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...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376711/ https://www.ncbi.nlm.nih.gov/pubmed/35965458 http://dx.doi.org/10.1098/rsta.2021.0315 |
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author | 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. |
author_facet | 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. |
author_sort | Panovska-Griffiths, J. |
collection | PubMed |
description | 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’. |
format | Online Article Text |
id | pubmed-9376711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-93767112022-08-22 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. Philos Trans A Math Phys Eng Sci Articles 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’. The Royal Society 2022-10-03 2022-08-15 /pmc/articles/PMC9376711/ /pubmed/35965458 http://dx.doi.org/10.1098/rsta.2021.0315 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles 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. Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title_full | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title_fullStr | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title_full_unstemmed | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title_short | Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions |
title_sort | statistical and agent-based modelling of the transmissibility of different sars-cov-2 variants in england and impact of different interventions |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9376711/ https://www.ncbi.nlm.nih.gov/pubmed/35965458 http://dx.doi.org/10.1098/rsta.2021.0315 |
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