Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
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Colleges, School and Institutes
The SARS-CoV-2 lineage B.1.1.7, designated variant of concern (VOC) 202012/01 by Public Health England1, was first identified in the UK in late summer to early autumn 20202. Whole-genome SARS-CoV-2 sequence data collected from community-based diagnostic testing for COVID-19 show an extremely rapid expansion of the B.1.1.7 lineage during autumn 2020, suggesting that it has a selective advantage. Here we show that changes in VOC frequency inferred from genetic data correspond closely to changes inferred by S gene target failures (SGTF) in community-based diagnostic PCR testing. Analysis of trends in SGTF and non-SGTF case numbers in local areas across England shows that B.1.1.7 has higher transmissibility than non-VOC lineages, even if it has a different latent period or generation time. The SGTF data indicate a transient shift in the age composition of reported cases, with cases of B.1.1.7 including a larger share of under 20-year-olds than non-VOC cases. We estimated time-varying reproduction numbers for B.1.1.7 and co-circulating lineages using SGTF and genomic data. The best-supported models did not indicate a substantial difference in VOC transmissibility among different age groups, but all analyses agreed that B.1.1.7 has a substantial transmission advantage over other lineages, with a 50% to 100% higher reproduction number.
Funding Information: Acknowledgements We thank all partners and contributors to the COG-UK consortium who are listed at https://www.cogconsortium.uk/about/. We thank the Sanger Covid Team (https:// www.sanger.ac.uk/covid-team) for data preparation and feedback on the manuscript. 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) and Genome Research Limited, operating as the Wellcome Sanger Institute. N.M.F., E.V., M.R. and S.B. acknowledge support from the MRC Centre for Global Infectious Disease Analysis (MR/R015600/1). R.J. and E.V. acknowledge funding from the European Commission (CoroNAb 101003653). D.J.L. and N.M.F. were supported by the NIHR VEEPED (PR-OD-1017-20002). S.B. received support from the NIHR BRC Imperial College NHS Trust Infection and COVID themes. S.B and N.M.F were supported by the UK Research and Innovation Fund MR/V038109/1. S.B. is supported by the Academy of Medical Sciences Springboard Award SBF004/1080. S.B. is supported by the Novo Nordisk Foundation Young Investigator Award NNF20OC0059309. O.R. and S.B. were supported by the Bill & Melinda Gates Foundation (OPP1175094, OPP1084362). Computational resources were provided by Amazon AWS and Microsoft AI for Health. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
|Number of pages||4|
|Early online date||25 Mar 2021|
|Publication status||Published - 13 May 2021|