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JDR Vol.16 No.1 pp. 12-15
(2021)
doi: 10.20965/jdr.2021.p0012

Note:

An Analysis of the COVID-19 Epidemic in Japan Using a Logistic Model

Kuniaki Miyamoto

University of Tsukuba
1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan

Corresponding author

Received:
October 29, 2020
Accepted:
December 28, 2020
Published:
January 30, 2021
Keywords:
logistic model, epidemic, pandemic, infectivity, COVID-19
Abstract

The COVID-19 pandemic has been persistent. For example, the number of infections increased exponentially since mid-September in Europe. The SIR, among other models, is used to examine and detail such epidemics and the changes they bring about. However, the application of the models requires that we fix the parameters to govern the processes; it is difficult to set them up appropriately, especially during new epidemic cases such as COVID-19. If we can limit the purpose of analysis to understand current epidemic situations, then it would be better to use simple models and limit the number of parameters. The logistic model is one of such suitable models, which can reflect the basic characteristics of an epidemic to provide information on the state and tendency of the epidemic based on little information. This research uses daily cases, deaths, and recoveries to analyze the epidemic and derives interesting results. The first wave of the epidemic, which ran from March to May, almost complies with the logistic model. In the case of the second wave, since mid-June, the results show that the rising phase has characteristics similar to those of the first wave. However, the phase of decline has different characteristics. Currently, in mid-October, it is almost in a state of equilibrium. This result means that the data used in this analysis show some characteristics of the statistical population of the “epidemic field.” However, while we consider the fact that infected persons must be isolated and hence removed from the “field,” it is suggested that the number of infected and recovered persons must be significantly larger than that of the reported cases. Nevertheless, it is difficult to evaluate the statistical characteristics of the “epidemic field” using the data, as they are not the results of “random sampling.”

Cite this article as:
Kuniaki Miyamoto, “An Analysis of the COVID-19 Epidemic in Japan Using a Logistic Model,” J. Disaster Res., Vol.16, No.1, pp. 12-15, 2021.
Data files:
References
  1. [1] W. O. Kermack and A. G. McKendrick, “A contribution to the mathematical theory of epidemic,” Proc. Roy. Soc., London, Series A, Vol.115, No.772, pp. 700-721, 1927.
  2. [2] H. Inaba, “Differential equation and mathematical epidemiology of infectious disease,” Mathematical Sciences, No.538, 2008 (in Japanese).
  3. [3] NewsDigest, https://newsdigest.jp/pages/coronavirus/ (in Japanese) [accessed October 16, 2020]
  4. [4] National Institute of Infectious Disease, “An epidemiological study of the SARS-CoV-2 genome in Japan,” April, 2020, https://www.niid.go.jp/niid/ja/basic-science/467-genome/9586-genome-2020-1.html (in Japanese) [accessed April 30, 2020]
  5. [5] National Institute of Infectious Disease, “An epidemiological study of the SARS-CoV-2 genome in Japan II,” August, 2020, https://www.niid.go.jp/niid/ja/basic-science/467-genome/9787-genome-2020-2.html (in Japanese) [accessed August 7, 2020]

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Last updated on Oct. 22, 2021