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Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference

OBJECTIVES: The Coronavirus disease 2019 (COVID-19) pandemic is causing significant damage to many nations. For mitigating its risk, Japan called on all elementary, junior high, and high schools nationwide to close beginning March 1, 2020. However, its effectiveness in decreasing the disease burden...

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Autores principales: Iwata, Kentaro, Doi, Asako, Miyakoshi, Chisato
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836901/
https://www.ncbi.nlm.nih.gov/pubmed/32745628
http://dx.doi.org/10.1016/j.ijid.2020.07.052
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author Iwata, Kentaro
Doi, Asako
Miyakoshi, Chisato
author_facet Iwata, Kentaro
Doi, Asako
Miyakoshi, Chisato
author_sort Iwata, Kentaro
collection PubMed
description OBJECTIVES: The Coronavirus disease 2019 (COVID-19) pandemic is causing significant damage to many nations. For mitigating its risk, Japan called on all elementary, junior high, and high schools nationwide to close beginning March 1, 2020. However, its effectiveness in decreasing the disease burden has not been investigated. METHODS: We used daily data of the COVID-19 and coronavirus infection incidence in Japan until March 31, 2020. Time-series analyses were conducted using the Bayesian method. Local linear trend models with interventional effects were constructed for the number of newly reported cases of COVID-19, including asymptomatic infections. We considered that the effects of the intervention started to appear nine days after the school closure. RESULTS: The intervention of school closure did not appear to decrease the incidence of coronavirus infection. If the effectiveness of school closure began on March 9, the mean coefficient α for the effectiveness of the measure was calculated to be 0.08 (95% confidence interval −0.36 to 0.65), and the actual reported cases were more than predicted, yet with a rather wide confidence interval. Sensitivity analyses using different dates also did not demonstrate the effectiveness of the school closure. DISCUSSION: School closure carried out in Japan did not show any mitigating effect on the transmission of novel coronavirus infection.
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spelling pubmed-78369012021-01-26 Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference Iwata, Kentaro Doi, Asako Miyakoshi, Chisato Int J Infect Dis Article OBJECTIVES: The Coronavirus disease 2019 (COVID-19) pandemic is causing significant damage to many nations. For mitigating its risk, Japan called on all elementary, junior high, and high schools nationwide to close beginning March 1, 2020. However, its effectiveness in decreasing the disease burden has not been investigated. METHODS: We used daily data of the COVID-19 and coronavirus infection incidence in Japan until March 31, 2020. Time-series analyses were conducted using the Bayesian method. Local linear trend models with interventional effects were constructed for the number of newly reported cases of COVID-19, including asymptomatic infections. We considered that the effects of the intervention started to appear nine days after the school closure. RESULTS: The intervention of school closure did not appear to decrease the incidence of coronavirus infection. If the effectiveness of school closure began on March 9, the mean coefficient α for the effectiveness of the measure was calculated to be 0.08 (95% confidence interval −0.36 to 0.65), and the actual reported cases were more than predicted, yet with a rather wide confidence interval. Sensitivity analyses using different dates also did not demonstrate the effectiveness of the school closure. DISCUSSION: School closure carried out in Japan did not show any mitigating effect on the transmission of novel coronavirus infection. The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. 2020-10 2020-07-31 /pmc/articles/PMC7836901/ /pubmed/32745628 http://dx.doi.org/10.1016/j.ijid.2020.07.052 Text en © 2020 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Iwata, Kentaro
Doi, Asako
Miyakoshi, Chisato
Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title_full Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title_fullStr Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title_full_unstemmed Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title_short Was school closure effective in mitigating coronavirus disease 2019 (COVID-19)? Time series analysis using Bayesian inference
title_sort was school closure effective in mitigating coronavirus disease 2019 (covid-19)? time series analysis using bayesian inference
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836901/
https://www.ncbi.nlm.nih.gov/pubmed/32745628
http://dx.doi.org/10.1016/j.ijid.2020.07.052
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