Trends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021
<p><strong>Background: </strong>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.</p> <p><strong>Aim: </strong>We charac...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
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Public Library of Science
2022
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| _version_ | 1797109038694006784 |
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| author | Eales, O Wang, H Haw, D Ainslie, KEC Walters, CE Atchison, C Cooke, G Barclay, W Ward, H Darzi, A Ashby, D Donnelly, CA Elliott, P Riley, S |
| author_facet | Eales, O Wang, H Haw, D Ainslie, KEC Walters, CE Atchison, C Cooke, G Barclay, W Ward, H Darzi, A Ashby, D Donnelly, CA Elliott, P Riley, S |
| author_sort | Eales, O |
| collection | OXFORD |
| description | <p><strong>Background: </strong>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.</p>
<p><strong>Aim: </strong>We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence.</p>
<p><strong>Methods: </strong>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 (<em>R</em><sub><em>t</em></sub>) 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 <em>R</em><sub><em>t</em></sub> of each relaxation of restrictions.</p>
<p><strong>Results: </strong>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 <em>R</em><sub><em>t</em></sub> 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 <em>R</em><sub><em>t</em></sub> 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.</p>
<p><strong>Conclusion: </strong>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.</p> |
| first_indexed | 2024-03-07T07:36:28Z |
| format | Journal article |
| id | oxford-uuid:6e072eb5-c09b-49c5-bb40-6122a6ebe5c2 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:36:28Z |
| publishDate | 2022 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | oxford-uuid:6e072eb5-c09b-49c5-bb40-6122a6ebe5c22023-03-08T15:35:28ZTrends in SARS-CoV-2 infection prevalence during England’s roadmap out of lockdown, January to July 2021Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:6e072eb5-c09b-49c5-bb40-6122a6ebe5c2EnglishSymplectic ElementsPublic Library of Science2022Eales, OWang, HHaw, DAinslie, KECWalters, CEAtchison, CCooke, GBarclay, WWard, HDarzi, AAshby, DDonnelly, CAElliott, PRiley, S<p><strong>Background: </strong>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.</p> <p><strong>Aim: </strong>We characterise how the lockdown and subsequent easing of restrictions affected trends in SARS-CoV-2 infection prevalence.</p> <p><strong>Methods: </strong>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 (<em>R</em><sub><em>t</em></sub>) 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 <em>R</em><sub><em>t</em></sub> of each relaxation of restrictions.</p> <p><strong>Results: </strong>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 <em>R</em><sub><em>t</em></sub> 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 <em>R</em><sub><em>t</em></sub> 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.</p> <p><strong>Conclusion: </strong>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.</p> |
| spellingShingle | Eales, O Wang, H Haw, D Ainslie, KEC Walters, CE Atchison, C Cooke, G Barclay, W Ward, H Darzi, A Ashby, D Donnelly, CA Elliott, P Riley, S 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 |
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