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Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021
BACKGROUND: Following 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. AIM: We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection pr...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728904/ https://www.ncbi.nlm.nih.gov/pubmed/36417468 http://dx.doi.org/10.1371/journal.pcbi.1010724 |
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author | Eales, Oliver Wang, Haowei Haw, David Ainslie, Kylie E. C. Walters, Caroline E. Atchison, Christina Cooke, Graham Barclay, Wendy Ward, Helen Darzi, Ara Ashby, Deborah Donnelly, Christl A. Elliott, Paul Riley, Steven |
author_facet | Eales, Oliver Wang, Haowei Haw, David Ainslie, Kylie E. C. Walters, Caroline E. Atchison, Christina Cooke, Graham Barclay, Wendy Ward, Helen Darzi, Ara Ashby, Deborah Donnelly, Christl A. Elliott, Paul Riley, Steven |
author_sort | Eales, Oliver |
collection | PubMed |
description | BACKGROUND: Following 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. AIM: We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence. METHODS: On 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 (R(t)) 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 R(t) of each relaxation of restrictions. RESULTS: Following 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 R(t) 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 R(t) increased steadily, though the increase due to these restrictions being relaxed was offset by the effects of vaccination and also affected by the rapid rise of Delta. There was a high degree of synchrony in the temporal patterns of prevalence between regions and age groups. CONCLUSION: High-resolution prevalence data fitted to P-splines allowed us to show that the lockdown was effective at reducing risk of infection with school holidays/closures playing a significant part. |
format | Online Article Text |
id | pubmed-9728904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-97289042022-12-08 Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 Eales, Oliver Wang, Haowei Haw, David Ainslie, Kylie E. C. Walters, Caroline E. Atchison, Christina Cooke, Graham Barclay, Wendy Ward, Helen Darzi, Ara Ashby, Deborah Donnelly, Christl A. Elliott, Paul Riley, Steven PLoS Comput Biol Research Article BACKGROUND: Following 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. AIM: We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence. METHODS: On 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 (R(t)) 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 R(t) of each relaxation of restrictions. RESULTS: Following 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 R(t) 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 R(t) increased steadily, though the increase due to these restrictions being relaxed was offset by the effects of vaccination and also affected by the rapid rise of Delta. There was a high degree of synchrony in the temporal patterns of prevalence between regions and age groups. CONCLUSION: High-resolution prevalence data fitted to P-splines allowed us to show that the lockdown was effective at reducing risk of infection with school holidays/closures playing a significant part. Public Library of Science 2022-11-23 /pmc/articles/PMC9728904/ /pubmed/36417468 http://dx.doi.org/10.1371/journal.pcbi.1010724 Text en © 2022 Eales et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Eales, Oliver Wang, Haowei Haw, David Ainslie, Kylie E. C. Walters, Caroline E. Atchison, Christina Cooke, Graham Barclay, Wendy Ward, Helen Darzi, Ara Ashby, Deborah Donnelly, Christl A. Elliott, Paul Riley, Steven Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title | Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title_full | Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title_fullStr | Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title_full_unstemmed | Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title_short | Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021 |
title_sort | trends in sars-cov-2 infection prevalence during england’s roadmap out of lockdown, january to july 2021 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728904/ https://www.ncbi.nlm.nih.gov/pubmed/36417468 http://dx.doi.org/10.1371/journal.pcbi.1010724 |
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