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Ohkusa, Y. and Sugawara, T. (2009) Simulation Model of Pandemic Influenza in the Whole of Japan. Journal of Japanese Infectious Disease, 62, 98-106.

has been cited by the following article:

  • TITLE: Simple Simulation for COVID-19 in Wuhan, Hubei, China to Predict Outbreak in Wuhan, the Initial Case in Wuhan, and the Epidemic in Japan as of 11 February, 2020

    AUTHORS: Junko Kurita, Tamie Sugawara, Yoshiyuki Sugishita, Yasushi Ohkusa

    KEYWORDS: COVID-19 Outbreak in Japan, SIR Model, Prediction, Mild Case, Asymptomatic Case

    JOURNAL NAME: Journal of Biosciences and Medicines, Vol.8 No.6, June 1, 2020

    ABSTRACT: Object: Prediction of the COVID-19 epidemic represents a matter of concern not only for public health or medicine but also for Earth’s general population. This study predicts outbreaks in Wuhan and in Japan as of 11 February, 2020.Method: We applied a simple SIR model to data published by Hubei public health authorities. Moreover, into the model, we incorporate mild and asymptomatic cases from experiences of Japanese residents of Wuhan up to the outbreak. Finally, we predict an outbreak in Japan based on 10,000 iterations of a simulation conducted under the assumption of infected people including mild cases visiting Japan according to the estimated distribution of patients in Wuhan since the date on which the initial case occurred to the date when travel from Wuhan to Japan was suspended. Results: Results suggest the basic reproduction number, R0, as 2.84; its 95% confidence interval (CI) was [2.35, 3.33]. The peak is estimated to be reached on March 11. Its 95% CI peak date is 29 February to 27 March. The 95% CI peak date in Japan is 26 April to 2 May. The greatest number of patients at the peak with severe symptoms was estimated as 858.3 thousand. Discussion and Conclusion: Our obtained R0 of 2.84 approximates an earlier estimate. We predicted the greatest number of patients at the peak with severe symptoms as 858.3 thousand in Japan. This number is 63% greater than the highest daily peak of influenza.