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Trends in SARS-CoV-2 infection prevalence during England's roadmap out of lockdown, January to July 2021
Oliver Eales; Haowei Wang; David Haw; Kylie E.C. Ainslie; Caroline E. Walters; Christina Atchison; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Deborah Ashby; Christl A Donnelly; Paul Elliott; Steven Riley.
Afiliação
  • Oliver Eales; Imperial College London
  • Haowei Wang; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
  • David Haw; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
  • Kylie E.C. Ainslie; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
  • Caroline E. Walters; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
  • Christina Atchison; School of Public Health, Imperial College London, UK
  • Graham Cooke; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic
  • Wendy Barclay; Department of Infectious Disease, Imperial College London, UK
  • Helen Ward; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear
  • Ara Darzi; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a
  • Deborah Ashby; School of Public Health, Imperial College London, UK
  • Christl A Donnelly; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
  • Paul Elliott; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear
  • Steven Riley; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc
Preprint em Inglês | medRxiv | ID: ppmedrxiv-22275900
ABSTRACT
BackgroundFollowing rapidly rising COVID-19 case numbers, England entered a national lockdown on 6 January 2021, with staged relaxations of restrictions from 8 March 2021 onwards. AimWe characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence. MethodsOn average, risk of infection is proportional to infection prevalence. The REal-time Assessment of Community Transmission-1 (REACT-1) study is a repeat cross-sectional study of over 98,000 people every round (rounds approximately monthly) that estimates infection prevalence in England. We used Bayesian P-splines to estimate prevalence and the time-varying reproduction number (Rt) nationally, regionally and by age group from round 8 (beginning 6 January 2021) to round 13 (ending 12 July 2021) of REACT-1. As a comparator, a separate segmented-exponential model was used to quantify the impact on Rt of each relaxation of restrictions. ResultsFollowing an initial plateau of 1.54% until mid-January, infection prevalence decreased until 13 May when it reached a minimum of 0.09%, before increasing until the end of the study to 0.76%. Following the first easing of restrictions, which included schools reopening, the reproduction number Rt increased by 82% (55%, 108%), but then decreased by 61% (82%, 53%) at the second easing of restrictions, which was timed to match the Easter school holidays. Following further relaxations of restrictions, the observed Rt increased steadily, though the increase due to these restrictions being relaxed was masked by the effects of vaccination and the rapid rise of Delta. There was a high degree of synchrony in the temporal patterns of prevalence between regions and age groups. ConclusionHigh-resolution prevalence data fitted to P-splines allowed us to show that the lockdown was highly effective at reducing risk of infection with school holidays/closures playing a significant part.
Licença
cc_by_nc_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Experimental_studies / Estudo observacional / Estudo prognóstico / Rct Idioma: Inglês Ano de publicação: 2022 Tipo de documento: Preprint
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