COVID-19 is a new deadly virus caused by the SARS-CoV-2 coronavirus, first identified in China at the end of
2019. Mathematical modeling is one of the most operative ways to comprehend and manage the growth of such
viruses. However, existing models have limitations, including challenges in mathematical analysis and a ten
dency to represent each virus individually. In this paper, a unified mathematical model is proposed to describe
the dynamics of Beta-CoV viruses in the human body, providing insights into their spread and control. This model
is adaptable to multiple coronaviruses, including MERS, SARS-CoV-2, COVID-19, and Omicron. The model pa
rameters are carefully adjusted to ensure suitability for each Beta-CoV variant. The stability of the proposed
model is analyzed using the Describing Function nonlinear technique. Additionally, the incubation periods of
different Beta-CoV viruses are investigated to determine which has the shortest duration in the human body. The
model is further extended to study the impact of antiviral drugs on viral dynamics. Finally, a sensitivity analysis
is conducted to identify the most influential parameters affecting viral behavior, which can help in developing
targeted interventions. |
