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

Oliver Eales, Andrew J. Page, Leonardo de Oliveira Martins, Haowei Wang, Barbara Bodinier, David Haw, Jakob Jonnerby, Christina Atchison, The COVID-19 Genomics UK (COG-UK) Consortium, Deborah Ashby, Wendy Barclay, Graham Taylor, Graham Cooke, Helen Ward, Ara Darzi, Steven Riley, Marc Chadeau-Hyam, Christl A Donnelly*, Paul Elliott*, Darren L. SmithMatthew Bashton, Gregory R. Young, Clare M. McCann, Andrew Nelson, Matthew R. Crown, John H. Henderson, Amy Hollis, William Stanley, Wen C. Yew

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number647
Number of pages17
JournalBMC Infectious Diseases
Volume22
Issue number1
Early online date27 Jul 2022
DOIs
Publication statusPublished - Dec 2022

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