Evidence map›Paper›PMID 35037252›Full record

SynthesisThe Cochrane database of systematic reviews2022

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

Shari Krishnaratne, Hannah Littlecott, Kerstin Sell, Jacob Burns, Julia E Rabe, Jan M Stratil, Tim Litwin, Clemens Kreutz, Michaela Coenen, Karin Geffert and 12 more

Open access · bronzeAbstract readSystematic Review
In one paragraph

Synthesis in The Cochrane database of systematic reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
8.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.

  1. Measures implemented in the school setting to contain the COVID-19 pandemic.The Cochrane database of systematic reviews · 2024
    Pooled it
  2. School food environment interventions for health and sustainability.The Cochrane database of systematic reviews · 2026
    Article
  3. Observational
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
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  14. Review
  15. Article
  16. Article
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  18. Article
  19. The impact of the COVID-19 pandemic on children's occupations.Hong Kong journal of occupational therapy : HKJOT · 2023
    Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 4 institutions in 2 countries.

Shari KrishnaratneInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Hannah LittlecottInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Kerstin SellInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Jacob BurnsInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Julia E RabeInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Jan M StratilInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Tim LitwinInstitute of Medical Biometry and Statistics (IMBI), Freiburg Center for Data Analytics and Modeling (FDM), Faculty of Medicine and Medical Center, Albert-Ludwig-University, Freiburg, Germany.
Clemens KreutzInstitute of Medical Biometry and Statistics (IMBI), Freiburg Center for Data Analytics and Modeling (FDM), Faculty of Medicine and Medical Center, Albert-Ludwig-University, Freiburg, Germany.
Michaela CoenenInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Karin GeffertInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Anna Helen BogerInstitute of Medical Biometry and Statistics (IMBI), Freiburg Center for Data Analytics and Modeling (FDM), Faculty of Medicine and Medical Center, Albert-Ludwig-University, Freiburg, Germany.
Ani MovsisyanInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Suzie KratzerInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Carmen KlingerInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Katharina WabnitzInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Brigitte StrahwaldInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Ben VerboomInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Eva RehfuessInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Renke L BiallasInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Caroline Jung-SieversInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Stephan VossInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Lisa M PfadenhauerInstitute for Medical Information Processing, Biometry and Epidemiology - IBE, Chair of Public Health and Health Services Research, LMU Munich, Munich, Germany.
Ludwig-Maximilians-Universität München · DEZimmer Biomet (Germany) · DEUniversity of Freiburg · DECardiff University · GB

Funding

Cancer Research UK 26532Medical Research Council MR/K023233/1
6 · The paper itself

Abstract

backgroundIn 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.

objectivesTo 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

methodsWe 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

resultsWe 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'

conclusionsOur 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.

Indexed as

COVID-19PandemicsHumansObservational Studies as TopicQuarantineSARS-CoV-2Schools

Identifiers

PMID35037252
PMCPMC8762709
OpenAlexW4205133794

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.