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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2022-01-01
|
| Series: | AIMS Public Health |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/publichealth.2022002?viewType=HTML |
| _version_ | 1811309852358606848 |
|---|---|
| author | Makoto Koizumi Motoaki Utamura Seiichi Kirikami |
| author_facet | Makoto Koizumi Motoaki Utamura Seiichi Kirikami |
| author_sort | Makoto Koizumi |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-13T09:49:22Z |
| format | Article |
| id | doaj.art-556787cf7729498eaca28fe2b8497c0d |
| institution | Directory Open Access Journal |
| issn | 2327-8994 |
| language | English |
| last_indexed | 2024-04-13T09:49:22Z |
| publishDate | 2022-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Public Health |
| spelling | doaj.art-556787cf7729498eaca28fe2b8497c0d2022-12-22T02:51:38ZengAIMS PressAIMS Public Health2327-89942022-01-0191172510.3934/publichealth.2022002Infection spread simulation technology in a mixed state of multi variant virusesMakoto Koizumi0Motoaki Utamura1Seiichi Kirikami21. PhD, Former researcher of Hitachi Ltd., Hitachi City, Ibaraki Prefecture, Japan2. PhD, PE, Former professor, Tokyo Institute of Technology, Tokyo, Japan3. Scholar, Former engineer of Hitachi Ltd., Hitachi City, Ibaraki Prefecture, JapanATLM (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.https://www.aimspress.com/article/doi/10.3934/publichealth.2022002?viewType=HTMLvariant coronaviruscovid-19epidemiological modelpredictionmulti-variant virusdelay differential equation |
| spellingShingle | Makoto Koizumi Motoaki Utamura Seiichi Kirikami Infection spread simulation technology in a mixed state of multi variant viruses AIMS Public Health variant coronavirus covid-19 epidemiological model prediction multi-variant virus delay differential equation |
| 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 | variant coronavirus covid-19 epidemiological model prediction multi-variant virus delay differential equation |
| url | https://www.aimspress.com/article/doi/10.3934/publichealth.2022002?viewType=HTML |
| work_keys_str_mv | AT makotokoizumi infectionspreadsimulationtechnologyinamixedstateofmultivariantviruses AT motoakiutamura infectionspreadsimulationtechnologyinamixedstateofmultivariantviruses AT seiichikirikami infectionspreadsimulationtechnologyinamixedstateofmultivariantviruses |