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Substantial Impact of School Closure on the Transmission Dynamics during the Pandemic Flu H1N1-2009 in Oita, Japan

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  • Shoko Kawano
  • Masayuki Kakehashi

Abstract

Background: School closure is considered as an effective measure to prevent pandemic influenza. Although Japan has implemented many class, grade, and whole school closures during the early stage of the pandemic 2009, the effectiveness of such a school closure has not been analysed appropriately. In addition, analysis based on evidence or data from a large population has yet to be performed. We evaluated the preventive effect of school closure against the pandemic (H1N1) 2009 and examined efficient strategies of reactive school closure. Materials and Methods: Data included daily reports of reactive school closures and the number of infected students in the pandemic in Oita City, Japan. We used a regression model that incorporated a time delay to analyse the daily data of school closure based on a time continuous susceptible-exposed-infected-removed model of infectious disease spread. The delay was due to the time-lag from transmission to case reporting. We simulated the number of students infected daily with and without school closure and evaluated the effectiveness. Results: The model with a 3-day delay from transmission to reporting yielded the best fit using R2 (the coefficient of determination). This result suggests that the recommended period of school closure is more than 4 days. Moreover, the effect of school closure in the simulation of school closure showed the following: the number of infected students decreased by about 24% at its peak, and the number of cumulative infected students decreased by about 8.0%. Conclusions: School closure was an effective intervention for mitigating the spread of influenza and should be implemented for more than 4 days. School closure has a remarkable impact on decreasing the number of infected students at the peak, but it does not substantially decrease the total number of infected students.

Suggested Citation

  • Shoko Kawano & Masayuki Kakehashi, 2015. "Substantial Impact of School Closure on the Transmission Dynamics during the Pandemic Flu H1N1-2009 in Oita, Japan," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-15, December.
    • Handle: RePEc:plo:pone00:0144839
    DOI: 10.1371/journal.pone.0144839
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    References listed on IDEAS

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    1. Simon Cauchemez & Alain-Jacques Valleron & Pierre-Yves Boëlle & Antoine Flahault & Neil M. Ferguson, 2008. "Estimating the impact of school closure on influenza transmission from Sentinel data," Nature, Nature, vol. 452(7188), pages 750-754, April.
    2. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
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    1. Margarida Rodrigues & Rui Silva & Mário Franco, 2021. "Teaching and Researching in the Context of COVID-19: An Empirical Study in Higher Education," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    2. María Alonso-García & Tamara María Garrido-Letrán & Alberto Sánchez-Alzola, 2021. "Impact of COVID-19 on Educational Sustainability. Initial Perceptions of the University Community of the University of Cádiz," Sustainability, MDPI, vol. 13(11), pages 1-20, May.
    3. Anna Verbytska & Olena Syzonenko, 2020. "Forced Virtualization for Research Activities at the Universities: Challenges and Solutions," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 12(2Sup1), pages 93-102, September.
    4. Margarida Rodrigues & Mário Franco & Rui Silva, 2020. "COVID-19 and Disruption in Management and Education Academics: Bibliometric Mapping and Analysis," Sustainability, MDPI, vol. 12(18), pages 1-25, September.
    5. Amodio, Emanuele & Battisti, Michele & Kourtellos, Andros & Maggio, Giuseppe & Maida, Carmelo Massimo, 2022. "Schools opening and Covid-19 diffusion: Evidence from geolocalized microdata," European Economic Review, Elsevier, vol. 143(C).

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