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Determining the optimal strategy for reopening schools, the impact of test and trace interventions, and the risk of occurrence of a second COVID-19 epidemic wave in the UK: a modelling study.

Identifieur interne : 002007 ( Main/Exploration ); précédent : 002006; suivant : 002008

Determining the optimal strategy for reopening schools, the impact of test and trace interventions, and the risk of occurrence of a second COVID-19 epidemic wave in the UK: a modelling study.

Auteurs : Jasmina Panovska-Griffiths [Royaume-Uni] ; Cliff C. Kerr [Australie] ; Robyn M. Stuart [Australie] ; Dina Mistry [États-Unis] ; Daniel J. Klein [États-Unis] ; Russell M. Viner [Royaume-Uni] ; Chris Bonell [Royaume-Uni]

Source :

RBID : pubmed:32758453

Descripteurs français

English descriptors

Abstract

BACKGROUND

As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.

METHODS

In this modelling study, we used Covasim, a stochastic individual-based model for transmission of SARS-CoV-2, calibrated to the UK epidemic. The model describes individuals' contact networks stratified into household, school, workplace, and community layers, and uses demographic and epidemiological data from the UK. We simulated six different scenarios, representing the combination of two school reopening strategies (full time and a part-time rota system with 50% of students attending school on alternate weeks) and three testing scenarios (68% contact tracing with no scale-up in testing, 68% contact tracing with sufficient testing to avoid a second COVID-19 wave, and 40% contact tracing with sufficient testing to avoid a second COVID-19 wave). We estimated the number of new infections, cases, and deaths, as well as the effective reproduction number (R) under different strategies. In a sensitivity analysis to account for uncertainties within the stochastic simulation, we also simulated infectiousness of children and young adults aged younger than 20 years at 50% relative to older ages (20 years and older).

FINDINGS

With increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active SARS-CoV-2 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound might be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of individuals with symptomatic infection would need to be tested and positive cases isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively. However, without these levels of testing and contact tracing, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a second wave that would peak in December, 2020, if schools open full-time in September, and in February, 2021, if a part-time rota system were adopted. In either case, the second wave would result in R rising above 1 and a resulting second wave of infections 2·0-2·3 times the size of the original COVID-19 wave. When infectiousness of children and young adults was varied from 100% to 50% of that of older ages, we still found that a comprehensive and effective test-trace-isolate strategy would be required to avoid a second COVID-19 wave.

INTERPRETATION

To prevent a second COVID-19 wave, relaxation of physical distancing, including reopening of schools, in the UK must be accompanied by large-scale, population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.

FUNDING

None.


DOI: 10.1016/S2352-4642(20)30250-9
PubMed: 32758453
PubMed Central: PMC7398659


Affiliations:


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<b>BACKGROUND</b>
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<p>As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.</p>
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<p>
<b>METHODS</b>
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<p>In this modelling study, we used Covasim, a stochastic individual-based model for transmission of SARS-CoV-2, calibrated to the UK epidemic. The model describes individuals' contact networks stratified into household, school, workplace, and community layers, and uses demographic and epidemiological data from the UK. We simulated six different scenarios, representing the combination of two school reopening strategies (full time and a part-time rota system with 50% of students attending school on alternate weeks) and three testing scenarios (68% contact tracing with no scale-up in testing, 68% contact tracing with sufficient testing to avoid a second COVID-19 wave, and 40% contact tracing with sufficient testing to avoid a second COVID-19 wave). We estimated the number of new infections, cases, and deaths, as well as the effective reproduction number (R) under different strategies. In a sensitivity analysis to account for uncertainties within the stochastic simulation, we also simulated infectiousness of children and young adults aged younger than 20 years at 50% relative to older ages (20 years and older).</p>
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<p>
<b>FINDINGS</b>
</p>
<p>With increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active SARS-CoV-2 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound might be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of individuals with symptomatic infection would need to be tested and positive cases isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively. However, without these levels of testing and contact tracing, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a second wave that would peak in December, 2020, if schools open full-time in September, and in February, 2021, if a part-time rota system were adopted. In either case, the second wave would result in R rising above 1 and a resulting second wave of infections 2·0-2·3 times the size of the original COVID-19 wave. When infectiousness of children and young adults was varied from 100% to 50% of that of older ages, we still found that a comprehensive and effective test-trace-isolate strategy would be required to avoid a second COVID-19 wave.</p>
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<p>
<b>INTERPRETATION</b>
</p>
<p>To prevent a second COVID-19 wave, relaxation of physical distancing, including reopening of schools, in the UK must be accompanied by large-scale, population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.</p>
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<p>
<b>FUNDING</b>
</p>
<p>None.</p>
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<Abstract>
<AbstractText Label="BACKGROUND">As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.</AbstractText>
<AbstractText Label="METHODS">In this modelling study, we used Covasim, a stochastic individual-based model for transmission of SARS-CoV-2, calibrated to the UK epidemic. The model describes individuals' contact networks stratified into household, school, workplace, and community layers, and uses demographic and epidemiological data from the UK. We simulated six different scenarios, representing the combination of two school reopening strategies (full time and a part-time rota system with 50% of students attending school on alternate weeks) and three testing scenarios (68% contact tracing with no scale-up in testing, 68% contact tracing with sufficient testing to avoid a second COVID-19 wave, and 40% contact tracing with sufficient testing to avoid a second COVID-19 wave). We estimated the number of new infections, cases, and deaths, as well as the effective reproduction number (R) under different strategies. In a sensitivity analysis to account for uncertainties within the stochastic simulation, we also simulated infectiousness of children and young adults aged younger than 20 years at 50% relative to older ages (20 years and older).</AbstractText>
<AbstractText Label="FINDINGS">With increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active SARS-CoV-2 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound might be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of individuals with symptomatic infection would need to be tested and positive cases isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively. However, without these levels of testing and contact tracing, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a second wave that would peak in December, 2020, if schools open full-time in September, and in February, 2021, if a part-time rota system were adopted. In either case, the second wave would result in R rising above 1 and a resulting second wave of infections 2·0-2·3 times the size of the original COVID-19 wave. When infectiousness of children and young adults was varied from 100% to 50% of that of older ages, we still found that a comprehensive and effective test-trace-isolate strategy would be required to avoid a second COVID-19 wave.</AbstractText>
<AbstractText Label="INTERPRETATION">To prevent a second COVID-19 wave, relaxation of physical distancing, including reopening of schools, in the UK must be accompanied by large-scale, population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.</AbstractText>
<AbstractText Label="FUNDING">None.</AbstractText>
<CopyrightInformation>Copyright © 2020 Elsevier Ltd. All rights reserved.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y">
<Author ValidYN="Y">
<LastName>Panovska-Griffiths</LastName>
<ForeName>Jasmina</ForeName>
<Initials>J</Initials>
<AffiliationInfo>
<Affiliation>Department of Applied Health Research and Institute for Global Health, University College London, London, UK; The Queen's College, University of Oxford, Oxford, UK. Electronic address: j.panovska-griffiths@ucl.ac.uk.</Affiliation>
</AffiliationInfo>
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<LastName>Kerr</LastName>
<ForeName>Cliff C</ForeName>
<Initials>CC</Initials>
<AffiliationInfo>
<Affiliation>Institute for Disease Modeling, Bellevue, WA, USA; Complex Systems Group, School of Physics, University of Sydney, Sydney, NSW, Australia.</Affiliation>
</AffiliationInfo>
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<LastName>Stuart</LastName>
<ForeName>Robyn M</ForeName>
<Initials>RM</Initials>
<AffiliationInfo>
<Affiliation>Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark; Burnet Institute, Melbourne, VIC, Australia.</Affiliation>
</AffiliationInfo>
</Author>
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<LastName>Mistry</LastName>
<ForeName>Dina</ForeName>
<Initials>D</Initials>
<AffiliationInfo>
<Affiliation>Institute for Disease Modeling, Bellevue, WA, USA.</Affiliation>
</AffiliationInfo>
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<LastName>Klein</LastName>
<ForeName>Daniel J</ForeName>
<Initials>DJ</Initials>
<AffiliationInfo>
<Affiliation>Institute for Disease Modeling, Bellevue, WA, USA.</Affiliation>
</AffiliationInfo>
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<LastName>Viner</LastName>
<ForeName>Russell M</ForeName>
<Initials>RM</Initials>
<AffiliationInfo>
<Affiliation>UCL Great Ormond St Institute of Child Health, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y">
<LastName>Bonell</LastName>
<ForeName>Chris</ForeName>
<Initials>C</Initials>
<AffiliationInfo>
<Affiliation>Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.</Affiliation>
</AffiliationInfo>
</Author>
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<Language>eng</Language>
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<PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
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<ArticleDate DateType="Electronic">
<Year>2020</Year>
<Month>08</Month>
<Day>03</Day>
</ArticleDate>
</Article>
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<Country>England</Country>
<MedlineTA>Lancet Child Adolesc Health</MedlineTA>
<NlmUniqueID>101712925</NlmUniqueID>
<ISSNLinking>2352-4642</ISSNLinking>
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<MeshHeading>
<DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName>
</MeshHeading>
<MeshHeading>
<DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName>
</MeshHeading>
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