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


Jackson, C; Mangtani, P; Hawker, J; Olowokure, B; Vynnycky, E; (2014) The effects of school closures on influenza outbreaks and pandemics: systematic review of simulation studies. PLoS One, 9 (5). e97297. ISSN 1932-6203 DOI: 10.1371/journal.pone.0097297

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Abstract

BACKGROUND School closure is a potential intervention during an influenza pandemic and has been investigated in many modelling studies. OBJECTIVES To systematically review the effects of school closure on influenza outbreaks as predicted by simulation studies. METHODS We 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. RESULTS School 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. CONCLUSIONS Simulation 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.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Research Centre: Centre for Maternal, Reproductive and Child Health (MARCH)
PubMed ID: 24830407
Web of Science ID: 336789500047
URI: http://researchonline.lshtm.ac.uk/id/eprint/1726154

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