Forecast Possible Risk for COVID-19 Epidemic Dissemination Under Current Control Strategies in Japan

Título

Forecast Possible Risk for COVID-19 Epidemic Dissemination Under Current Control Strategies in Japan

Autor

Zhongxiang Chen, Jun Yang, Binxiang Dai

Descripción

COVID-19 has globally spread to over 4 million people and the epidemic situation in Japan is very serious. The purpose of this research was to assess the risk of COVID-19 epidemic dissemination in Japan by estimating the current state of epidemic dissemination and providing some epidemic prevention and control recommendations. Firstly, the period from 6 January to 31 March 2020 was divided into four stages and the relevant parameters were estimated according to the imported cases in Japan. The basic reproduction number of the current stage is 1.954 (95% confidence interval (CI) 1.851–2.025), which means COVID-19 will spread quickly, and the self-healing rate of Japanese is about 0.495 (95% CI 0.437–0.506), with small variations in the four stages. Secondly, the results were applied to the actual reported cases from 1 to 5 April 2020, verifying the reliability of the estimated data using the accumulated reported cases located within the 95% confidence interval and the relative error of forecast data of five days being less than 2 . 5 % . Thirdly, considering the medical resources in Japan, the times the epidemic beds and ventilators become fully occupied are predicted as 5 and 15 May 2020, respectively. Keeping with the current situation, the final death toll in Japan may reach into the millions. Finally, based on experience with COVID-19 prevention and control in China, robust measures such as nationwide shutdown, store closures, citizens isolating themselves at home, and increasing PCR testing would quickly and effectively prevent COVID-19 spread.

Fecha

2020

Materia

covid-19, basic reproduction number, SEIHR epidemic model

Identificador

10.3390/ijerph17113872

Fuente

Epidemiology and Health

Editor

Korean Society of Epidemiology

Cobertura

Medicine

Archivos

https://socictopen.socict.org/files/to_import/pdfs/cfabc4421cf743cc1c000e585337271c.pdf

Colección

Citación

Zhongxiang Chen, Jun Yang, Binxiang Dai, “Forecast Possible Risk for COVID-19 Epidemic Dissemination Under Current Control Strategies in Japan,” SOCICT Open, consulta 17 de abril de 2026, https://www.socictopen.socict.org/items/show/10303.

Formatos de Salida

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