Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China
COVID-19 is a disease caused by infection with the virus 2019-nCoV, a single-stranded RNA virus. During the infection and transmission processes, the virus evolves and mutates rapidly, though the disease has been quickly controlled in Wuhan by ‘Fangcang’ hospitals. To model the virulence evolution,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-12-01
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| Series: | Journal of Biological Dynamics |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17513758.2021.2020916 |
| _version_ | 1818754739861454848 |
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| author | Xi-Chao Duan Xue-Zhi Li Maia Martcheva Sanling Yuan |
| author_facet | Xi-Chao Duan Xue-Zhi Li Maia Martcheva Sanling Yuan |
| author_sort | Xi-Chao Duan |
| collection | DOAJ |
| description | COVID-19 is a disease caused by infection with the virus 2019-nCoV, a single-stranded RNA virus. During the infection and transmission processes, the virus evolves and mutates rapidly, though the disease has been quickly controlled in Wuhan by ‘Fangcang’ hospitals. To model the virulence evolution, in this paper, we formulate a new age structured epidemic model. Under the tradeoff hypothesis, two special scenarios are used to study the virulence evolution by theoretical analysis and numerical simulations. Results show that, before ‘Fangcang’ hospitals, two scenarios are both consistent with the data. After ‘Fangcang’ hospitals, Scenario I rather than Scenario II is consistent with the data. It is concluded that the transmission pattern of COVID-19 in Wuhan obey Scenario I rather than Scenario II. Theoretical analysis show that, in Scenario I, shortening the value of L (diagnosis period) can result in an enormous selective pressure on the evolution of 2019-nCoV. |
| first_indexed | 2024-12-18T05:28:03Z |
| format | Article |
| id | doaj.art-c20c69b88fa24b5e844ef253696b9f1e |
| institution | Directory Open Access Journal |
| issn | 1751-3758 1751-3766 |
| language | English |
| last_indexed | 2024-12-18T05:28:03Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Biological Dynamics |
| spelling | doaj.art-c20c69b88fa24b5e844ef253696b9f1e2022-12-21T21:19:30ZengTaylor & Francis GroupJournal of Biological Dynamics1751-37581751-37662022-12-01161142810.1080/17513758.2021.20209162020916Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, ChinaXi-Chao Duan0Xue-Zhi Li1Maia Martcheva2Sanling Yuan3University of Shanghai for Science and TechnologyHenan Normal UniversityUniversity of FloridaUniversity of Shanghai for Science and TechnologyCOVID-19 is a disease caused by infection with the virus 2019-nCoV, a single-stranded RNA virus. During the infection and transmission processes, the virus evolves and mutates rapidly, though the disease has been quickly controlled in Wuhan by ‘Fangcang’ hospitals. To model the virulence evolution, in this paper, we formulate a new age structured epidemic model. Under the tradeoff hypothesis, two special scenarios are used to study the virulence evolution by theoretical analysis and numerical simulations. Results show that, before ‘Fangcang’ hospitals, two scenarios are both consistent with the data. After ‘Fangcang’ hospitals, Scenario I rather than Scenario II is consistent with the data. It is concluded that the transmission pattern of COVID-19 in Wuhan obey Scenario I rather than Scenario II. Theoretical analysis show that, in Scenario I, shortening the value of L (diagnosis period) can result in an enormous selective pressure on the evolution of 2019-nCoV.http://dx.doi.org/10.1080/17513758.2021.20209162019-ncovage structured modelcovid-19virulence evolution‘fangcang’ hospitals |
| spellingShingle | Xi-Chao Duan Xue-Zhi Li Maia Martcheva Sanling Yuan Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China Journal of Biological Dynamics 2019-ncov age structured model covid-19 virulence evolution ‘fangcang’ hospitals |
| title | Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China |
| title_full | Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China |
| title_fullStr | Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China |
| title_full_unstemmed | Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China |
| title_short | Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China |
| title_sort | using an age structured covid 19 epidemic model and data to model virulence evolution in wuhan china |
| topic | 2019-ncov age structured model covid-19 virulence evolution ‘fangcang’ hospitals |
| url | http://dx.doi.org/10.1080/17513758.2021.2020916 |
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