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Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey.
Lythgoe, Katrina A; Golubchik, Tanya; Hall, Matthew; House, Thomas; Cahuantzi, Roberto; MacIntyre-Cockett, George; Fryer, Helen; Thomson, Laura; Nurtay, Anel; Ghafani, Mahan; Buck, David; Green, Angie; Trebes, Amy; Piazza, Paolo; Lonie, Lorne J; Studley, Ruth; Rourke, Emma; Smith, Darren; Bashton, Matthew; Nelson, Andrew; Crown, Matthew; McCann, Clare; Young, Gregory R; Andre Nunes Dos Santos, Rui; Richards, Zack; Tariq, Adnan; Fraser, Christophe; Diamond, Ian; Barrett, Jeff; Walker, Ann Sarah; Bonsall, David.
Afiliação
  • Lythgoe KA; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Golubchik T; Department of Biology, University of Oxford, Oxford OX1 3SZ, UK.
  • Hall M; Pandemic Sciences Institute, University of Oxford, Oxford, UK.
  • House T; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Cahuantzi R; Sydney Infectious Diseases Institute (Sydney ID), School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
  • MacIntyre-Cockett G; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Fryer H; Department of Mathematics, University of Manchester, Manchester M13 9PL, UK.
  • Thomson L; Department of Mathematics, University of Manchester, Manchester M13 9PL, UK.
  • Nurtay A; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Ghafani M; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Buck D; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Green A; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Trebes A; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Piazza P; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Lonie LJ; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Studley R; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Rourke E; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Smith D; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Bashton M; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK.
  • Nelson A; Office for National Statistics, Newport, UK.
  • Crown M; Office for National Statistics, Newport, UK.
  • McCann C; The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Nothumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Young GR; The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Nothumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Andre Nunes Dos Santos R; The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Nothumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Richards Z; The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Nothumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Tariq A; Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Fraser C; Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Diamond I; Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK.
  • Bonsall D; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
Proc Biol Sci ; 290(2009): 20231284, 2023 10 25.
Article em En | MEDLINE | ID: mdl-37848057
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Epidemias / COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Epidemias / COVID-19 Limite: Humans País/Região como assunto: Europa Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Reino Unido