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Transmission of SARS-CoV-2 Lineage B.1.1.7 in England: Insights from linking epidemiological and genetic data
Erik Volz; Swapnil Mishra; Meera Chand; Jeffrey C Barrett; Robert Johnson; Lily Geidelberg; Wes R Hinsley; Daniel J Laydon; Gavin Dabrera; Áine O'Toole; Roberto Amato; Manon Ragonnet-Cronin; Ian Harrison; Ben Jackson; Cristina V Ariani; Olivia Boyd; Nick Loman; John T McCrone; Sonia Gonçalves; David Jorgensen; Richard Myers; Verity Hill; David K Jackson; Katy Gaythorpe; Natalie Groves; John Sillitoe; Dominic P Kwiatkowski; - COG-UK; Seth Flaxman; Oliver Ratman; Samir Bhatt; Susan Hopkins; Axel Gandy; Andrew Rambaut; Neil M Ferguson.
Afiliación
  • Erik Volz; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Swapnil Mishra; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Meera Chand; National Infection Service, Public Health England
  • Jeffrey C Barrett; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • Robert Johnson; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Lily Geidelberg; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Wes R Hinsley; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Daniel J Laydon; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Gavin Dabrera; National Infection Service, Public Health England
  • Áine O'Toole; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
  • Roberto Amato; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • Manon Ragonnet-Cronin; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Ian Harrison; National Infection Service, Public Health England
  • Ben Jackson; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
  • Cristina V Ariani; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • Olivia Boyd; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Nick Loman; National Infection Service, Public Health England
  • John T McCrone; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
  • Sonia Gonçalves; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • David Jorgensen; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Richard Myers; National Infection Service, Public Health England
  • Verity Hill; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
  • David K Jackson; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • Katy Gaythorpe; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Natalie Groves; National Infection Service, Public Health England
  • John Sillitoe; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • Dominic P Kwiatkowski; Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
  • - COG-UK;
  • Seth Flaxman; Department of Mathematics, Imperial College London, London, UK
  • Oliver Ratman; Department of Mathematics, Imperial College London, London, UK
  • Samir Bhatt; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
  • Susan Hopkins; National Infection Service, Public Health England
  • Axel Gandy; Department of Mathematics, Imperial College London, London, UK
  • Andrew Rambaut; Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
  • Neil M Ferguson; MRC Centre for Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20249034
ABSTRACT
The SARS-CoV-2 lineage B.1.1.7, now designated Variant of Concern 202012/01 (VOC) by Public Health England, originated in the UK in late Summer to early Autumn 2020. We examine epidemiological evidence for this VOC having a transmission advantage from several perspectives. First, whole genome sequence data collected from community-based diagnostic testing provides an indication of changing prevalence of different genetic variants through time. Phylodynamic modelling additionally indicates that genetic diversity of this lineage has changed in a manner consistent with exponential growth. Second, we find 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. Third, we examine growth trends in SGTF and non-SGTF case numbers at local area level across England, and show that the VOC has higher transmissibility than non-VOC lineages, even if the VOC has a different latent period or generation time. Available SGTF data indicate a shift in the age composition of reported cases, with a larger share of under 20 year olds among reported VOC than non-VOC cases. Fourth, we assess the association of VOC frequency with independent estimates of the overall SARS-CoV-2 reproduction number through time. Finally, we fit a semi-mechanistic model directly to local VOC and non-VOC case incidence to estimate the reproduction numbers over time for each. There is a consensus among all analyses that the VOC has a substantial transmission advantage, with the estimated difference in reproduction numbers between VOC and non-VOC ranging between 0.4 and 0.7, and the ratio of reproduction numbers varying between 1.4 and 1.8. We note that these estimates of transmission advantage apply to a period where high levels of social distancing were in place in England; extrapolation to other transmission contexts therefore requires caution.
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Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo de estudio: Estudio diagnóstico / Estudio observacional Idioma: Inglés Año: 2021 Tipo del documento: Preprint
Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Tipo de estudio: Estudio diagnóstico / Estudio observacional Idioma: Inglés Año: 2021 Tipo del documento: Preprint
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