Modeling the Within-Host Dynamics of SARS-CoV-2 Infection Based on Antiviral Treatment

Tianqi Song, Yishi Wang, Xi Gu () and Sijia Qiao
Additional contact information
Tianqi Song: School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
Yishi Wang: Shanghai Institute of Aerospace System Engineering, Shanghai 201100, China
Xi Gu: School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China
Sijia Qiao: Department of Finance, Shanghai National Accounting Institute, Shanghai 201702, China

Mathematics, 2023, vol. 11, issue 16, 1-19

Abstract: The COVID-19 pandemic has highlighted the profound impact of the SARS-CoV-2 virus as a significant threat to human health. There is an urgent need to develop a comprehensive understanding of the current outbreak by studying the dynamics of the virus within the human body. In this research, we present a mathematical model that explores the progression of SARS-CoV-2 infection, taking into account both the innate and adaptive immune responses. We calculated the basic reproduction number and analyzed the stability of the equilibria. Additionally, we demonstrated the existence of a periodic solution through numerical simulations. By conducting a global sensitivity analysis, we determined the significance of the model parameters and investigated the influence of key parameters on viral load. The results emphasized the crucial roles of cytokines and antibodies in shaping the dynamics of SARS-CoV-2. Furthermore, we evaluated the effectiveness of antiviral treatment in controlling the dynamics of SARS-CoV-2 infection. Our findings revealed a direct relationship between the basic reproduction number and the impact of antiviral treatment. To evaluate the effect of antiviral treatment on viral load, we conducted numerical simulations.

Keywords: within-host model; SARS-CoV-2 infection; immune response; antiviral treatment (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/16/3485/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/16/3485/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:16:p:3485-:d:1215668

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().