Abstract
The COVID-19 pandemic caused by SARS-CoV-2 has posed significant to the global health
challenges. Understanding the disease dynamics at the within-host level remains one of the
challenging factors in disease system analysis. This study is aimed at understanding the withinhost
dynamics of SARS-CoV-2 infection using coupled nasal and lung cell infection, incorporating
immune response and treatment options through mathematical models. We formulated
and analyzed a coupled mathematical model for the within-host dynamics of SARS-CoV-2 in
nasal and lung cells with and without treatment. The disease-free equilibrium is stable when
R0 <1 and unstable whenR0 >1, and the endemic equilibrium point is stable when the Routh-
Hurwitz stability conditions are met. We used the FME R package to estimate parameters for
our model from synthetic data, and we used them to perform numerical simulations. Numerical
results showed that increasing the efficacy of both considered drugs can reduce the viral load
in both the nasal and the lung cells. These findings also revealed that increasing the efficacy
values of the drugs can lead to the clearance of the virus; however, using the pharmacokinetics
properties proved that the drugs can only reduce the viral load and not clear the virus. The
results from natural drug resistance showed that the drugs can only be effective when taken
simultaneously with perfect adherence when the properties of the drug do not change. They
also revealed that the effect of sub-optimal adherence to both drugs, along with natural drug
resistance, increased the risk of severe infection.