Using an age-structured COVID-19 epidemic model and data to model virulence evolution in Wuhan, China
| Autor: | Xi-Chao Duan, Xue-Zhi Li, Maia Martcheva, Sanling Yuan |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Biological Dynamics, Vol 16, Iss 1, Pp 14-28 (2022) |
| Druh dokumentu: | article |
| ISSN: | 1751-3758 1751-3766 17513758 |
| DOI: | 10.1080/17513758.2021.2020916 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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