Vöhringer, HS;
Sanderson, T;
Sinnott, M;
De Maio, N;
Nguyen, T;
Goater, R;
Schwach, F;
Harrison, I;
Hellewell, J;
Ariani, CV;
et al.
Vöhringer, HS; Sanderson, T; Sinnott, M; De Maio, N; Nguyen, T; Goater, R; Schwach, F; Harrison, I; Hellewell, J; Ariani, CV; Gonçalves, S; Jackson, DK; Johnston, I; Jung, AW; Saint, C; Sillitoe, J; Suciu, M; Goldman, N; Panovska-Griffiths, J; Wellcome Sanger Institute COVID-19 Surveillance Team; COVID-19 Genomics UK (COG-UK) Consortium*; Birney, E; Volz, E; Funk, S; Kwiatkowski, D; Chand, M; Martincorena, I; Barrett, JC; Gerstung, M
(2021)
Genomic reconstruction of the SARS-CoV-2 epidemic in England.
Nature, 600 (7889).
pp. 506-511.
ISSN 1476-4687
https://doi.org/10.1038/s41586-021-04069-y
SGUL Authors: Laing, Kenneth
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Abstract
The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.
Item Type: | Article | |||||||||||||||||||||
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Additional Information: | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2021 | |||||||||||||||||||||
Keywords: | Amino Acid Substitution, COVID-19, England, Epidemiological Monitoring, Genome, Viral, Genomics, Humans, Molecular Epidemiology, Mutation, Quarantine, SARS-CoV-2, Spatio-Temporal Analysis, Spike Glycoprotein, Coronavirus, Wellcome Sanger Institute COVID-19 Surveillance Team, COVID-19 Genomics UK (COG-UK) Consortium*, MD Multidisciplinary, General Science & Technology | |||||||||||||||||||||
SGUL Research Institute / Research Centre: | Academic Structure > Infection and Immunity Research Institute (INII) | |||||||||||||||||||||
Journal or Publication Title: | Nature | |||||||||||||||||||||
ISSN: | 1476-4687 | |||||||||||||||||||||
Language: | eng | |||||||||||||||||||||
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Publisher License: | Creative Commons: Attribution 4.0 | |||||||||||||||||||||
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PubMed ID: | 34649268 | |||||||||||||||||||||
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URI: | https://openaccess.sgul.ac.uk/id/eprint/114023 | |||||||||||||||||||||
Publisher's version: | https://doi.org/10.1038/s41586-021-04069-y |
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