# Ordinary differential equation models of SARS-CoV-2 replication dynamics and antiviral drug efficacies

## TL;DR

This paper reviews mathematical models of SARS-CoV-2 replication and antiviral effects to better understand virus-host interactions and improve treatment strategies.

## Contribution

The paper provides a systematic review of ODE models for SARS-CoV-2, highlighting model limitations and data gaps.

## Key findings

- TCL ODE models offer insights into SARS-CoV-2 replication dynamics.
- Incorporating antiviral treatments into models reveals drug efficacy patterns.
- Structural identifiability issues and limited datasets hinder model accuracy.

## Abstract

There is a critical need for precise analysis of virus–host interactions to improve our understanding of infection processes. The integration of quantitative measurements with dynamic mathematical modeling has changed how we perceive cellular infection processes, offering profound insights into how viruses function at the cellular level. Here, we systematically review target cell-limited (TCL) ordinary differential equation (ODE) models related to SARS-CoV-2. We examine the spectrum of available models from basic TCL frameworks to more complex models incorporating antiviral treatments—and highlight key findings, discuss strengths and limitations, and identify a shortage of comprehensive datasets, emphasizing structural identifiability issues.