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SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

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Title: SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2
Authors: Eales, O
Wang, H
Bodinier, B
Haw, D
Jonnerby, J
Atchison, C
Ashby, D
Barclay, W
Taylor, G
Cooke, G
Ward, H
Darzi, A
Riley, S
Chadeau, M
Donnelly, C
Elliott, P
Item Type: Journal Article
Abstract: Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September - 27 September 2021) and 15 (19 October - 5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI, 8%-23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.
Issue Date: 27-Jul-2022
Date of Acceptance: 4-Jul-2022
URI: http://hdl.handle.net/10044/1/98322
DOI: 10.1186/s12879-022-07628-4
ISSN: 1471-2334
Publisher: BioMed Central
Journal / Book Title: BMC Infectious Diseases
Volume: 22
Copyright Statement: 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Sponsor/Funder: Department of Health
Department of Health
Imperial College Healthcare NHS Trust- BRC Funding
Medical Research Council (MRC)
Cancer Research UK
Commission of the European Communities
Commission of the European Communities
Medical Research Council (MRC)
Imperial College Healthcare NHS Trust- BRC Funding
Wellcome Trust
National Institute for Health Research
Imperial College Healthcare NHS Trust: Research Capability Funding (RCF)
Funder's Grant Number: n/a
‘Mechanomics’ PRC project grant 22184
Keywords: Science & Technology
Life Sciences & Biomedicine
Infectious Diseases
Delta variant
Genetic diversity
Transmission advantage
Delta variant
Genetic diversity
Transmission advantage
COVID-19 Genomics UK (COG-UK) Consortium
0605 Microbiology
1103 Clinical Sciences
1108 Medical Microbiology
Publication Status: Published
Article Number: ARTN 647
Appears in Collections:Department of Surgery and Cancer
Department of Infectious Diseases
Faculty of Medicine
Institute of Global Health Innovation
School of Public Health

This item is licensed under a Creative Commons License Creative Commons