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

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 infecte...

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Autores principales: Koizumi, Makoto, Utamura, Motoaki, Kirikami, Seiichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIMS Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755968/
https://www.ncbi.nlm.nih.gov/pubmed/35071665
http://dx.doi.org/10.3934/publichealth.2022002
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author Koizumi, Makoto
Utamura, Motoaki
Kirikami, Seiichi
author_facet Koizumi, Makoto
Utamura, Motoaki
Kirikami, Seiichi
author_sort Koizumi, Makoto
collection PubMed
description 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.
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spelling pubmed-87559682022-01-20 Infection spread simulation technology in a mixed state of multi variant viruses Koizumi, Makoto Utamura, Motoaki Kirikami, Seiichi AIMS Public Health Research Article 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. AIMS Press 2021-11-05 /pmc/articles/PMC8755968/ /pubmed/35071665 http://dx.doi.org/10.3934/publichealth.2022002 Text en © 2022 the Author(s), licensee AIMS Press https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) )
spellingShingle Research Article
Koizumi, Makoto
Utamura, Motoaki
Kirikami, Seiichi
Infection spread simulation technology in a mixed state of multi variant viruses
title Infection spread simulation technology in a mixed state of multi variant viruses
title_full Infection spread simulation technology in a mixed state of multi variant viruses
title_fullStr Infection spread simulation technology in a mixed state of multi variant viruses
title_full_unstemmed Infection spread simulation technology in a mixed state of multi variant viruses
title_short Infection spread simulation technology in a mixed state of multi variant viruses
title_sort infection spread simulation technology in a mixed state of multi variant viruses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8755968/
https://www.ncbi.nlm.nih.gov/pubmed/35071665
http://dx.doi.org/10.3934/publichealth.2022002
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