Within host dynamics of SARS-CoV-2 in humans: Modeling immune responses and antiviral treatments

TL;DR

This paper develops a mathematical model of SARS-CoV-2 within-host dynamics, analyzing immune responses and antiviral treatments, providing insights into viral load control and informing drug development strategies.

Contribution

It introduces a novel within-host SARS-CoV-2 model incorporating immune responses, analyzes its equilibrium, and evaluates antiviral and vaccination strategies using real patient data.

Findings

Blocking virus production reduces viral load more effectively.

Vaccination helps control infection but is less immediate than antiviral drugs.

Model calibration aligns well with observed viral load data.

Abstract

In December 2019, a newly discovered SARS-CoV-2 virus was emerged from China and propagated worldwide as a pandemic. In the absence of preventive medicine or a ready to use vaccine, mathematical models can provide useful scientific insights about transmission patterns and targets for drug development. In this study, we propose a within-host mathematical model of SARS-CoV-2 infection considering innate and adaptive immune responses. We analyze the equilibrium points of the proposed model and obtain an expression of the basic reproduction number. We then numerically show the existence of a transcritical bifurcation. The proposed model is calibrated to real viral load data of two COVID-19 patients. Using the estimated parameters, we perform global sensitivity analysis with respect to the peak of viral load. Finally, we study the efficacy of antiviral drugs and vaccination on the dynamics of SARS-CoV-2 infection. Our results suggest that blocking the production of the virus by infected cells decreases the viral load more than reducing the infection rate of healthy cells. Vaccination is also found useful but during the vaccine development phase, blocking virus production from infected cells can be targeted for antiviral drug development.