TY - JOUR
T1 - Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey
AU - Wellcome Sanger Institute COVID-19 Surveillance Team
AU - Lythgoe, Katrina A
AU - Golubchik, Tanya
AU - Hall, Matthew
AU - House, Thomas
AU - Cahuantzi, Roberto
AU - MacIntyre-Cockett, George
AU - Fryer, Helen
AU - Thomson, Laura
AU - Nurtay, Anel
AU - Ghafani, Mahan
AU - Buck, David
AU - Green, Angie
AU - Trebes, Amy
AU - Piazza, Paolo
AU - Lonie, Lorne J
AU - Studley, Ruth
AU - Rourke, Emma
AU - Smith, Darren
AU - Bashton, Matthew
AU - Nelson, Andrew
AU - Crown, Matthew
AU - McCann, Clare
AU - Young, Gregory R
AU - Andre Nunes Dos Santos, Rui
AU - Richards, Zack
AU - Tariq, Adnan
AU - Fraser, Christophe
AU - Diamond, Ian
AU - Barrett, Jeff
AU - Walker, Ann Sarah
AU - Bonsall, David
N1 - Funding information: The CIS is funded by the Department of Health and Social Care with in-kind support from the Welsh Government, the Department of Health on behalf of the Northern Ireland Government and the Scottish Government. 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) (grant code: MC_PC_19027) and Genome Research Limited, operating as the Wellcome Sanger Institute. The authors acknowledge the support of the NHS Test and Trace Genomics Programme through sequencing of SARS-CoV-2 genomes analysed in this study. The computational analysis was supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z with additional support from the NIHR Oxford BRC. A.S.W. is supported by the National Institute for Health Research Health Protection Research Unit (NIHR HPRU) in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford in partnership with the UK Health Security Agency (UK HSA) (grant no. NIHR200915) and the NIHR Oxford Biomedical Research Centre, and is an NIHR Senior Investigator. T.H. is supported by the Royal Society and Alan Turing Institute for Data Science and Artificial Intelligence. K.A.L. is supported by the Royal Society and the Wellcome Trust (grant no. 107652/Z/15/Z) and the Li Ka Shing Foundation. The views expressed are those of the authors and not necessarily those of the National Health Service, NIHR, Department of Health, or UKHSA.
PY - 2023/10/25
Y1 - 2023/10/25
N2 - The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.
AB - The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.
KW - Coronavirus (COVID-19) Infection Survey
KW - SARS-CoV-2
KW - United Kingdom
KW - evolution
UR - https://www.scopus.com/pages/publications/85174749398
U2 - 10.1098/rspb.2023.1284
DO - 10.1098/rspb.2023.1284
M3 - Article
C2 - 37848057
SN - 0962-8452
VL - 290
JO - Proceedings of the Royal Society B: Biological Sciences
JF - Proceedings of the Royal Society B: Biological Sciences
IS - 2009
M1 - 20231284
ER -
SDG 3 Good Health and Well-being