Infection spread simulation technology in a mixed state of multi variant viruses

Makoto Koizumi; Motoaki Utamura; Seiichi Kirikami; Makoto Koizumi; Motoaki Utamura; Seiichi Kirikami

doi:10.3934/publichealth.2022002

AIMS Public Health

2022, Volume 9, Issue 1: 17-25. doi: 10.3934/publichealth.2022002

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Research article

Infection spread simulation technology in a mixed state of multi variant viruses

1.
PhD, Former researcher of Hitachi Ltd., Hitachi City, Ibaraki Prefecture, Japan
2.
PhD, PE, Former professor, Tokyo Institute of Technology, Tokyo, Japan
3.
Scholar, Former engineer of Hitachi Ltd., Hitachi City, Ibaraki Prefecture, Japan

Received: 16 August 2021 Accepted: 01 November 2021 Published: 05 November 2021

ATLM (Apparent Time Lag Model) was extended to simulate the spread of infection in a mixed state of the variant virus and original wild type. It is applied to the 4th wave of infection spread in Tokyo, and (1) the 4th wave bottoms out near the end of the state of emergency, and the number of infected people increases again. (2) The rate of increase will be mainly by d strain (L452R) virus, while the increase by a strain (N501Y) virus will be suppressed. (3) It is anticipated that the infection will spread during the Olympic Games. (4) When variant viruses compete, the infection of highly infectious virus rises sharply while the infection by weakly infectious ones has converged. (5) It is effective as an infection control measure to find an infected person early and shorten the period from infection to quarantine by PCR test or antigen test as a measure other than the vaccine.
- variant coronavirus,
- COVID-19,
- epidemiological model,
- prediction,
- multi-variant virus,
- delay differential equation
Citation: Makoto Koizumi, Motoaki Utamura, Seiichi Kirikami. Infection spread simulation technology in a mixed state of multi variant viruses[J]. AIMS Public Health, 2022, 9(1): 17-25. doi: 10.3934/publichealth.2022002

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Abstract

ATLM (Apparent Time Lag Model) was extended to simulate the spread of infection in a mixed state of the variant virus and original wild type. It is applied to the 4th wave of infection spread in Tokyo, and (1) the 4th wave bottoms out near the end of the state of emergency, and the number of infected people increases again. (2) The rate of increase will be mainly by d strain (L452R) virus, while the increase by a strain (N501Y) virus will be suppressed. (3) It is anticipated that the infection will spread during the Olympic Games. (4) When variant viruses compete, the infection of highly infectious virus rises sharply while the infection by weakly infectious ones has converged. (5) It is effective as an infection control measure to find an infected person early and shorten the period from infection to quarantine by PCR test or antigen test as a measure other than the vaccine.

Acknowledgments

MK is the former researcher of Hitachi Ltd., MU is the former professor of Tokyo Institute of Technology and SK is the former engineer of Hitachi Ltd. M. Koizumi developed the epidemiological model. M. Utamura verified the numerical results. S. Kirikami identified parameter values from data. All authors have read and agreed to the published version of manuscript.

Data availability

We used time-series data of COVID-19 for March 1 through June 10, 2021 in Tokyo [15].

Conflict of interest

The authors declare that they have no conflict of interest related to this report or the study it describes.

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