Evidence map›Paper›PMID 24830407›Full record

SynthesisPloS one2014

The effects of school closures on influenza outbreaks and pandemics: systematic review of simulation studies.

Charlotte Jackson, Punam Mangtani, Jeremy Hawker, Babatunde Olowokure, Emilia Vynnycky

Abstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 5 pooled it
–field-weighted citation impact
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

80 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Impact of COVID-19 on School Populations and Associated Factors: A Systematic Review.International journal of environmental research and public health · 2022
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  17. Assessing the effect of school closures on the spread of COVID-19 in Zurich.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2022
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20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Charlotte JacksonDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom; Statistics, Modelling and Economics Department, Public Health England, London, United Kingdom.
Punam MangtaniDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Jeremy HawkerField Epidemiology Services, Public Health England, Birmingham, United Kingdom.
Babatunde OlowokureWest Midlands Public Health England Centre, Public Health England, Birmingham, United Kingdom.
Emilia VynnyckyDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom; Statistics, Modelling and Economics Department, Public Health England, London, United Kingdom.

Funding

Department of Health RTF/01/038
6 · The paper itself

Abstract

backgroundSchool closure is a potential intervention during an influenza pandemic and has been investigated in many modelling studies.

objectivesTo systematically review the effects of school closure on influenza outbreaks as predicted by simulation studies.

methodsWe searched Medline and Embase for relevant modelling studies published by the end of October 2012, and handsearched key journals. We summarised the predicted effects of school closure on the peak and cumulative attack rates and the duration of the epidemic. We investigated how these predictions depended on the basic reproduction number, the timing and duration of closure and the assumed effects of school closures on contact patterns.

resultsSchool closures were usually predicted to be most effective if they caused large reductions in contact, if transmissibility was low (e.g. a basic reproduction number <2), and if attack rates were higher in children than in adults. The cumulative attack rate was expected to change less than the peak, but quantitative predictions varied (e.g. reductions in the peak were frequently 20-60% but some studies predicted >90% reductions or even increases under certain assumptions). This partly reflected differences in model assumptions, such as those regarding population contact patterns.

conclusionsSimulation studies suggest that school closure can be a useful control measure during an influenza pandemic, particularly for reducing peak demand on health services. However, it is difficult to accurately quantify the likely benefits. Further studies of the effects of reactive school closures on contact patterns are needed to improve the accuracy of model predictions.

Indexed as

Disease OutbreaksPandemicsAdolescentChildChild, PreschoolCommunicable Disease ControlComputer SimulationHumansIncidenceInfluenza, HumanModels, TheoreticalSchoolsTime Factors

Identifiers

PMID24830407
PMCPMC4022492

What OpenQuestion holds

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LicenceCC BY
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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.