School closure and management practices during coronavirus outbreaks including COVID-19: a rapid systematic review
Open accessAbstract
In response to the coronavirus disease 2019 (COVID-19) pandemic, 107 countries had implemented national school closures by March 18, 2020. It is unknown whether school measures are effective in coronavirus outbreaks (eg, due to severe acute respiratory syndrome [SARS], Middle East respiratory syndrome, or COVID-19). We undertook a systematic review by searching three electronic databases to identify what is known about the effectiveness of school closures and other school social distancing practices during coronavirus outbreaks. We included 16 of 616 identified articles. School closures were deployed rapidly across mainland China and Hong Kong for COVID-19. However, there are no data on the relative contribution of school closures to transmission control. Data from the SARS outbreak in mainland China, Hong Kong, and Singapore suggest that school closures did not contribute to the control of the epidemic. Modelling studies of SARS produced conflicting results. Recent modelling studies of COVID-19 predict that school closures alone would prevent only 2-4% of deaths, much less than other social distancing interventions. Policy makers need to be aware of the equivocal evidence when considering school closures for COVID-19, and that combinations of social distancing measures should be considered. Other less disruptive social distancing interventions in schools require further consideration if restrictive social distancing policies are implemented for long periods.
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The association between mental health and the pandemic may be explained by international lockdown measures leading to increased social isolation.
“This association may be explained by the international lockdown measures (e.g., school closures, non-essential business shutdowns, and enforced social distancing measures) that were implemented to reduce the spread of the virus, which led to an increase in social isolation amongst the general public [34].”
From Mental Health Impact of COVID-19 among Children and College Students: A Systematic Review (2023) · cites this paper as [34]
COVID-19 has resulted in far more widespread impact on the everyday lives of children and adolescents around the world than SARS, MERS or H1N1.
“COVID-19 has resulted in far more widespread impact on the everyday lives of children and adolescents around the world than SARS, MERS or H1N1.”
From Exploring the Impact of COVID-19 on Mental Health Outcomes in Children and Adolescents: A Systematic Review (2020) · cites this paper as [12]
The United Nations Educational, Scientific and Cultural Organisation approximated that school closures affected 862 million children and young people, an estimated half of the global student population.
“For example, the United Nations (UN) Educational, Scientific and Cultural Organisation approximated that school closures affected 862 million children and young people, an estimated half of the global student population [12].”
From Exploring the Impact of COVID-19 on Mental Health Outcomes in Children and Adolescents: A Systematic Review (2020) · cites this paper as [12]
Four review articles have identified negative implications of quarantine affecting public mental health and access to education.
“Four review articles have identified negative implications of quarantine affecting public mental health and access to education.9–12”
From Social consequences of mass quarantine during epidemics: a systematic review with implications for the COVID-19 response (2020) · cites this paper as [12]
For many children and young people, the pandemic includes psychological impacts relating to isolation and disrupted educational provision and attainment at critical timepoints.
“For many CYP, this includes psychological impacts relating to isolation and disrupted educational provision and attainment at critical timepoints [6,7].”
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- Authors
- Viner, R. M., Russell, S. J., Croker, H., Packer, J., Ward, J., Stansfield, C., Mytton, O., Bonell, C., & Booy, R.
- Affiliations
- University College London (GB)
- University of Cambridge (GB)
- London School of Hygiene & Tropical Medicine (GB)
- The University of Sydney (AU)
- Corresponding author
- Viner, Russell M
- ORCID
- Venue
- The Lancet Child & Adolescent Health
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 4
- Issue
- 5
- Pages
- 397-404
- ISSN
- 2352-4642 (ISSN-L)
- PMC
- PMC7270629
- OpenAlex
- W3015107971
- Cited by
- 2,213
- References
- 41
- Citations by year
- 2026: 44 · 2025: 91 · 2024: 146 · 2023: 281 · 2022: 451 · 2021: 741 · 2020: 456 · 2019: 2 · 2013: 1
- FWCI
- 19.35
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Lancet Child & Adolescent Health (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- The Sydney eScholarship Repository (The University of Sydney) (submittedVersion)
- Funders
- National Institute for Health and Care Research (ACF-2010-13-011, CL-2017-14-004, NF-SI-0515-10085)
- Medical Research Council (MR/R00160X/1)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Social Sciences › Education › Education during COVID-19 pandemic
- Keywords
- school closures, COVID-19 pandemic, SARS, MERS, coronavirus outbreak, social distancing, epidemic control, transmission control, school-based intervention, epidemic modeling, public health policy
- MeSH terms
- COVID-19, Adolescent, Child, Child, Preschool, Disease Outbreaks, Humans, Influenza, Human, Pneumonia, Viral, Schools, Time Factors, Coronavirus, Coronavirus Infections, Disease Transmission, Infectious, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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