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      The Effects of School Closures on Influenza Outbreaks and Pandemics: Systematic Review of Simulation Studies

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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.

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          Most cited references73

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          Mitigation strategies for pandemic influenza in the United States.

          Recent human deaths due to infection by highly pathogenic (H5N1) avian influenza A virus have raised the specter of a devastating pandemic like that of 1917-1918, should this avian virus evolve to become readily transmissible among humans. We introduce and use a large-scale stochastic simulation model to investigate the spread of a pandemic strain of influenza virus through the U.S. population of 281 million individuals for R(0) (the basic reproductive number) from 1.6 to 2.4. We model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social mobility (including school closure and travel restrictions) have on the timing and magnitude of this spread. Our simulations demonstrate that, in a highly mobile population, restricting travel after an outbreak is detected is likely to delay slightly the time course of the outbreak without impacting the eventual number ill. For R(0) < 1.9, our model suggests that the rapid production and distribution of vaccines, even if poorly matched to circulating strains, could significantly slow disease spread and limit the number ill to <10% of the population, particularly if children are preferentially vaccinated. Alternatively, the aggressive deployment of several million courses of influenza antiviral agents in a targeted prophylaxis strategy may contain a nascent outbreak with low R(0), provided adequate contact tracing and distribution capacities exist. For higher R(0), we predict that multiple strategies in combination (involving both social and medical interventions) will be required to achieve similar limits on illness rates.
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            Transmissibility of 1918 pandemic influenza

            The 1918 influenza pandemic killed 20–40 million people worldwide 1 , and is seen as a worst-case scenario for pandemic planning. Like other pandemic influenza strains, the 1918 A/H1N1 strain spread extremely rapidly. A measure of transmissibility and of the stringency of control measures required to stop an epidemic is the reproductive number, which is the number of secondary cases produced by each primary case 2 . Here we obtained an estimate of the reproductive number for 1918 influenza by fitting a deterministic SEIR (susceptible-exposed-infectious-recovered) model to pneumonia and influenza death epidemic curves from 45 US cities: the median value is less than three. The estimated proportion of the population with A/H1N1 immunity before September 1918 implies a median basic reproductive number of less than four. These results strongly suggest that the reproductive number for 1918 pandemic influenza is not large relative to many other infectious diseases 2 . In theory, a similar novel influenza subtype could be controlled. But because influenza is frequently transmitted before a specific diagnosis is possible and there is a dearth of global antiviral and vaccine stores, aggressive transmission reducing measures will probably be required. Supplementary information The online version of this article (doi:10.1038/nature03063) contains supplementary material, which is available to authorized users.
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              Estimating the impact of school closure on influenza transmission from Sentinel data.

              The threat posed by the highly pathogenic H5N1 influenza virus requires public health authorities to prepare for a human pandemic. Although pre-pandemic vaccines and antiviral drugs might significantly reduce illness rates, their stockpiling is too expensive to be practical for many countries. Consequently, alternative control strategies, based on non-pharmaceutical interventions, are a potentially attractive policy option. School closure is the measure most often considered. The high social and economic costs of closing schools for months make it an expensive and therefore controversial policy, and the current absence of quantitative data on the role of schools during influenza epidemics means there is little consensus on the probable effectiveness of school closure in reducing the impact of a pandemic. Here, from the joint analysis of surveillance data and holiday timing in France, we quantify the role of schools in influenza epidemics and predict the effect of school closure during a pandemic. We show that holidays lead to a 20-29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults. Holidays prevent 16-18% of seasonal influenza cases (18-21% in children). By extrapolation, we find that prolonged school closure during a pandemic might reduce the cumulative number of cases by 13-17% (18-23% in children) and peak attack rates by up to 39-45% (47-52% in children). The impact of school closure would be reduced if it proved difficult to maintain low contact rates among children for a prolonged period.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                15 May 2014
                : 9
                : 5
                : e97297
                Affiliations
                [1 ]Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
                [2 ]Statistics, Modelling and Economics Department, Public Health England, London, United Kingdom,
                [3 ]Field Epidemiology Services, Public Health England, Birmingham, United Kingdom
                [4 ]West Midlands Public Health England Centre, Public Health England, Birmingham, United Kingdom
                Arizona State University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: BO JH CJ PM EV. Performed the experiments: CJ EV. Analyzed the data: CJ EV PM. Wrote the paper: CJ EV PM. Wrote the generic research plan: JH. Developed the detailed methodology: CJ EV PM. Contributed to interpretation of data: JH BO. Critically revised manuscript: JH BO.

                Article
                PONE-D-13-43115
                10.1371/journal.pone.0097297
                4022492
                24830407
                8cc53f89-1c58-479d-a27f-ac9d7420b1a8
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 October 2013
                : 17 April 2014
                Page count
                Pages: 10
                Funding
                This work was partially funded by the Health Protection Agency (now known as Public Health England). Charlotte Jackson was supported by an NIHR Research Training Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Population Modeling
                Infectious Disease Modeling
                Medicine and Health Sciences
                Epidemiology
                Infectious Disease Epidemiology
                Infectious Diseases
                Viral Diseases
                Influenza
                Infectious Disease Control
                Medical Humanities
                Evidence-Based Medicine
                Public and Occupational Health
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Research Design
                Clinical Research Design

                Uncategorized
                Uncategorized

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