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. 2022 Jan 17;1(1):CD015029.
doi: 10.1002/14651858.CD015029.

Measures implemented in the school setting to contain the COVID-19 pandemic

Affiliations

Measures implemented in the school setting to contain the COVID-19 pandemic

Shari Krishnaratne et al. Cochrane Database Syst Rev. .

Update in

  • Measures implemented in the school setting to contain the COVID-19 pandemic.
    Littlecott H, Krishnaratne S, Burns J, Rehfuess E, Sell K, Klinger C, Strahwald B, Movsisyan A, Metzendorf MI, Schoenweger P, Voss S, Coenen M, Müller-Eberstein R, Pfadenhauer LM. Littlecott H, et al. Cochrane Database Syst Rev. 2024 May 2;5(5):CD015029. doi: 10.1002/14651858.CD015029.pub2. Cochrane Database Syst Rev. 2024. PMID: 38695826 Free PMC article.

Abstract

Background: In response to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the impact of coronavirus disease 2019 (COVID-19), governments have implemented a variety of measures to control the spread of the virus and the associated disease. Among these, have been measures to control the pandemic in primary and secondary school settings.

Objectives: To assess the effectiveness of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic, with particular focus on the different types of measures implemented in school settings and the outcomes used to measure their impacts on transmission-related outcomes, healthcare utilisation outcomes, other health outcomes as well as societal, economic, and ecological outcomes. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and the Educational Resources Information Center, as well as COVID-19-specific databases, including the Cochrane COVID-19 Study Register and the WHO COVID-19 Global literature on coronavirus disease (indexing preprints) on 9 December 2020. We conducted backward-citation searches with existing reviews.

Selection criteria: We considered experimental (i.e. randomised controlled trials; RCTs), quasi-experimental, observational and modelling studies assessing the effects of measures implemented in the school setting to safely reopen schools, or keep schools open, or both, during the COVID-19 pandemic. Outcome categories were (i) transmission-related outcomes (e.g. number or proportion of cases); (ii) healthcare utilisation outcomes (e.g. number or proportion of hospitalisations); (iii) other health outcomes (e.g. physical, social and mental health); and (iv) societal, economic and ecological outcomes (e.g. costs, human resources and education). We considered studies that included any population at risk of becoming infected with SARS-CoV-2 and/or developing COVID-19 disease including students, teachers, other school staff, or members of the wider community. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles, abstracts and full texts. One review author extracted data and critically appraised each study. One additional review author validated the extracted data. To critically appraise included studies, we used the ROBINS-I tool for quasi-experimental and observational studies, the QUADAS-2 tool for observational screening studies, and a bespoke tool for modelling studies. We synthesised findings narratively. Three review authors made an initial assessment of the certainty of evidence with GRADE, and several review authors discussed and agreed on the ratings.

Main results: We included 38 unique studies in the analysis, comprising 33 modelling studies, three observational studies, one quasi-experimental and one experimental study with modelling components. Measures fell into four broad categories: (i) measures reducing the opportunity for contacts; (ii) measures making contacts safer; (iii) surveillance and response measures; and (iv) multicomponent measures. As comparators, we encountered the operation of schools with no measures in place, less intense measures in place, single versus multicomponent measures in place, or closure of schools. Across all intervention categories and all study designs, very low- to low-certainty evidence ratings limit our confidence in the findings. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the model structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to deviations from intended interventions or missing data. Across all categories, few studies reported on implementation or described how measures were implemented. Where we describe effects as 'positive', the direction of the point estimate of the effect favours the intervention(s); 'negative' effects do not favour the intervention. We found 23 modelling studies assessing measures reducing the opportunity for contacts (i.e. alternating attendance, reduced class size). Most of these studies assessed transmission and healthcare utilisation outcomes, and all of these studies showed a reduction in transmission (e.g. a reduction in the number or proportion of cases, reproduction number) and healthcare utilisation (i.e. fewer hospitalisations) and mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 11 modelling studies and two observational studies assessing measures making contacts safer (i.e. mask wearing, cleaning, handwashing, ventilation). Five studies assessed the impact of combined measures to make contacts safer. They assessed transmission-related, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed a reduction in transmission, and a reduction in hospitalisations; however, studies showed mixed or negative effects on societal, economic and ecological outcomes (i.e. fewer number of days spent in school). We identified 13 modelling studies and one observational study assessing surveillance and response measures, including testing and isolation, and symptomatic screening and isolation. Twelve studies focused on mass testing and isolation measures, while two looked specifically at symptom-based screening and isolation. Outcomes included transmission, healthcare utilisation, other health, and societal, economic and ecological outcomes. Most of these studies showed effects in favour of the intervention in terms of reductions in transmission and hospitalisations, however some showed mixed or negative effects on societal, economic and ecological outcomes (e.g. fewer number of days spent in school). We found three studies that reported outcomes relating to multicomponent measures, where it was not possible to disaggregate the effects of each individual intervention, including one modelling, one observational and one quasi-experimental study. These studies employed interventions, such as physical distancing, modification of school activities, testing, and exemption of high-risk students, using measures such as hand hygiene and mask wearing. Most of these studies showed a reduction in transmission, however some showed mixed or no effects. As the majority of studies included in the review were modelling studies, there was a lack of empirical, real-world data, which meant that there were very little data on the actual implementation of interventions.

Authors' conclusions: Our review suggests that a broad range of measures implemented in the school setting can have positive impacts on the transmission of SARS-CoV-2, and on healthcare utilisation outcomes related to COVID-19. The certainty of the evidence for most intervention-outcome combinations is very low, and the true effects of these measures are likely to be substantially different from those reported here. Measures implemented in the school setting may limit the number or proportion of cases and deaths, and may delay the progression of the pandemic. However, they may also lead to negative unintended consequences, such as fewer days spent in school (beyond those intended by the intervention). Further, most studies assessed the effects of a combination of interventions, which could not be disentangled to estimate their specific effects. Studies assessing measures to reduce contacts and to make contacts safer consistently predicted positive effects on transmission and healthcare utilisation, but may reduce the number of days students spent at school. Studies assessing surveillance and response measures predicted reductions in hospitalisations and school days missed due to infection or quarantine, however, there was mixed evidence on resources needed for surveillance. Evidence on multicomponent measures was mixed, mostly due to comparators. The magnitude of effects depends on multiple factors. New studies published since the original search date might heavily influence the overall conclusions and interpretation of findings for this review.

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Conflict of interest statement

RB: grant/contract from Bundesministerium für Bildung und Forschung

AB: none

JB: grant/contract from German Federal Ministry of Education and Research

MC: grant/contract from Bundesministerium für Bildung und Forschung

KG: grant/contract from German Federal Ministry of Education and Research; Board Member of the German Public Health Association

CJS: German Federal Ministry of Education and Research; I work as a physician (primary tasks: education and research) at the Chair of Public Health, LMU Munich

CaK: grant/contract from German Federal Ministry of Education and Research SuK: grant/contract from Bundesministerium für Bildung und Forschung ClK: none ShK: grant/contract from German Federal Ministry of Education and Research HL: none TL: grant/contract from German Federal Ministry of Education AM: grant/contract from German Federal Ministry of Education and Research LMP: grant/contract from German Federal Ministry of Education and Research JR: grant/contract from German Federal Ministry of Education and Research; I declare being first author of a study on the psychosocial burden in parents of school‐aged children during different phases of the Covid‐19 pandemic in Germany, that was submitted to, but is not yet published by the Journal “Bundesgesundheitsblatt” and might be eligible in future updates of the review. Data for this study were derived from the Covid‐19 Snapshot Monitoring (COSMO) project (https://projekte.uni-erfurt.de/cosmo2020/web/). COSMO is a joint project by the University of Erfurt, the Robert‐Koch‐Institute, the German Federal Agency for Health Education (BZgA), the Leibniz Institute for Psychology, the Science Media Centre, the Bernhard Nocht Institute for Tropical Medicine and the Yale Institute for Public Health. Besides funding from these institutions, funding of the COSMO project derives from the Klaus Tschira Foundation, the Ministry of Economy, Research and Digital Society of Thuringia as well as the state chancellery of Thuringia. ER: grant/contract from Bundesministerium für Bildung und Forschung; a member of the scientific advisory board of the Robert Koch Institute and the Bavarian Health and Food Safety Authority that have both issued guidance on schooling during COVID‐19, but have not been involved with developing this guidance; a member of the WHO Regional Office for Europe’s Technical Advisory Group on Schooling during COVID‐19 and, in this role, is involved with advising the WHO Regional Office for Europe on the issue KS:grant/contract from German Federal Ministry of Education and Research BS: grant/contract from German Federal Ministry of Education and Research JS: grant/contract from Bundesministerium für Bildung und Forschung BV: grant/contract from German Federal Ministry of Education and Research SV: grant/contract from German Federal Ministry of Education and Research KW: grant/contract from German Federal Ministry for Education and Research

RB, KG, CaK, SuK, AM, LMP, JR, ER, KS, BS, JS, BV, SV, KW declare being part of the scientific secretariat that supports the development of a living interdisciplinary, evidence‐based and consensus‐based guideline on measures to prevent and control SARS‐CoV‐2 transmission in schools, registered with the Association of the Scientific Medical Societies (AWMF) in Germany (www.awmf.org/en/clinical-practice-guidelines/detail/anmeldung/1/ll/027-076.html).

CJS, AM and ER are involved in the conduct of an ongoing study that, after completion, is likely to be eligible for inclusion in the review (COVID Kids Bavaria, funded by the State of Bavaria, Germany).

Figures

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1
A priori logic model
2
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A posteriori logic model
3
3
Evidence gap map in which each square represents the case in which a single included study evaluated a type of school measure (rows) against an outcome category (columns); additionally, the study type is provided (colour)
4
4
PRISMA flow chart
5
5
PRISMA flow chart: top‐up search
6
6
Geographical distribution of included studies

References

References to studies included in this review

Alvarez 2020 {published data only}
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Germann 2020 {published data only}
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Gill 2020 {published data only}
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Head 2020 {published data only}
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Hoehl 2020 {published data only}
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Isphording 2020 {published data only}
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Jones 2020 {published data only}
    1. Jones RD.COVID-19 trends in Florida K-12 schools, August 10 – November 14, 2020. medRxiv 2020. [DOI: 10.1101/2020.11.30.20241224] - DOI
Kaiser 2020 {published data only}
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Keeling 2020 {published data only}
    1. Keeling MJ, Tildesley MJ, Atkins BD, Penman B, Southall E, Guyver-Fletcher G, et al.The impact of school reopening on the spread of COVID-19 in England. medRxiv 2020. [DOI: 10.1101/2020.06.04.20121434] - DOI - PMC - PubMed
Kraay 2020 {published data only}
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Landeros 2020 {published data only}
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Lazebnik 2020 {published data only}
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Lee 2020 {published data only}
    1. Lee B, Hanley JP, Nowak S, Bates JH, Hébert-Dufresne L.Modeling the impact of school reopening on SARS-CoV-2 transmission using contact structure data from Shanghai. BMC Public Health 2020;20(1):1713. [PMID: ] - PMC - PubMed
Lyng 2020 {published data only}
    1. Lyng GD, Sheils NE, Kennedy CJ, Griffin D, Berke EM.Identifying optimal COVID-19 testing strategies for schools and businesses: balancing testing frequency, individual test technology, and cost. medRxiv 2020. [DOI: 10.1101/2020.10.11.20211011] - DOI - PMC - PubMed
Mauras 2020 {published data only}
    1. Mauras S, Cohen-Addad V, Duboc G, Dupré la Tour M, Frasca P, Mathieu C, et al.Mitigating COVID-19 outbreaks in workplaces and schools by hybrid telecommuting. medRxiv 2020. [DOI: 10.1101/2020.11.09.20228007] - DOI - PMC - PubMed
Monod 2020 {published data only}
    1. Monod M, Blenkinsop A, Xi X, Hebert D, Bershan S, Tietze S, et al.Report 32: Age groups that sustain resurging COVID-19 epidemics in the United States. medRxiv 2020. [DOI: 10.1101/2020.09.18.20197376] - DOI - PMC - PubMed
Munday 2020 {published data only}
    1. Munday JD, Sherratt K, Meakin S, Endo A, Pearson CA, Hellewell J, et al.Implications of the school-household network structure on SARS-CoV-2 transmission under different school reopening strategies in England. medRxiv 2020. [DOI: 10.1101/2020.08.21.20167965] - DOI - PMC - PubMed
Naimark 2020 {published data only}
    1. Naimark D, Mishra S, Barrett K, Khan YA, Mac S, Ximenes R, et al.The potential impact of school closure relative to community-based non-pharmaceutical interventions on COVID-19 cases in Ontario, Canada. medRxiv 2020. [DOI: 10.1101/2020.11.18.20234351] - DOI
Panovska‐Griffiths 2020a {published data only}
    1. Panovska-Griffiths J, Kerr CC, Stuart RM, Mistry D, Klein DJ, Viner RM, et al.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. Lancet Child & Adolescent Health 2020;4(11):817-27. [PMID: ] - PMC - PubMed
Panovska‐Griffiths 2020b {published data only}
    1. Panovska-Griffiths J, Kerr CC, Waites W, Stuart RM, Mistry D, Foster D, et al.Modelling the potential impact of mask use in schools and society on COVID-19 control in the UK. medRxiv 2020. [DOI: 10.1101/2020.09.28.20202937] - DOI - PMC - PubMed
Phillips 2020 {published data only}
    1. Phillips B, Browne DT, Anand M, Bauch CT.Model-based projections for COVID-19 outbreak size and student-days lost to closure in Ontario childcare centers and primary schools. medRxiv 2020. [DOI: 10.1101/2020.08.07.20170407] - DOI - PMC - PubMed
Rozhnova 2020 {published data only}
    1. Rozhnova G, Dorp CH, Bruijning-Verhagen P, Bootsma MC, de Wijgert JH, Bonten MJ, et al.Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic. medRxiv 2020. [DOI: 10.1101/2020.12.07.20245506] - DOI - PMC - PubMed
Shelley 2020 {published data only}
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Simonsen 2020 {published data only}
    1. Simonsen AB, Ruge IF, Quaade AS, Johansen JD, Thyssen JP, Zachariae C.High incidence of hand eczema in Danish schoolchildren following intensive hand hygiene during the COVID-19 pandemic: a nationwide questionnaire study. British Journal of Dermatology 2020;183(5):975-6. [PMID: ] - PMC - PubMed
Sruthi 2020 {published data only}
    1. Sruthi CK, Biswal MR, Saraswat B, Joshi H, Prakash MK.How policies on restaurants, bars, nightclubs, masks, schools, and travel influenced Swiss COVID-19 reproduction ratios. medRxiv 2020. [DOI: 10.1101/2020.10.11.20210641] - DOI
Tupper 2020 {published data only}
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Vlachos 2020 {published data only}
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Williams 2020 {published data only}
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Zhang 2020 {published data only}
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References to studies excluded from this review

Anchordoqui 2020 {published data only}
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Balabdaoui 2020 {published data only}
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Bracis 2020 {published data only}
    1. Bracis C, Burns E, Moore M, Swan D, Reeves DB, Schiffer JT, et al.Widespread testing, case isolation and contact tracing may allow safe school reopening with continued moderate physical distancing: a modeling analysis of King County, WA data. medRxiv 2020. [DOI: 10.1101/2020.08.14.20174649] - DOI - PMC - PubMed
Brooks‐Pollock 2021 {published data only}
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Buonsenso 2020 {published data only}
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Coletti 2020 {published data only}
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Di Domenico 2020b {published data only}
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Ehrhardt 2020 {published data only}
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Gandolfi 2021 {published data only}
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Garchitorena 2020 {published data only}
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Johnson 2020 {published data only}
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Kim 2020 {published data only}
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Macartney 2020 {published data only}
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McBride 2020 {published data only}
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McBryde 2020 {published data only}
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Sneppen 2020 {published data only}
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Stage 2021 {published data only}
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Stein‐Zamir 2020 {published data only}
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Wibbens 2020 {published data only}
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Yoon 2020 {published data only}
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References to studies awaiting assessment

Asgary 2021 {published data only}
    1. Asgary A, Cojocaru MG, Najafabadi MM, Wu J.Simulating preventative testing of SARS-CoV-2 in schools: policy implications. BMC Public Health 2021;21(1):125. [PMID: ] - PMC - PubMed
Bilinski 2021 {published data only}
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