In response to the profound impact of the SARS-CoV-2 pandemic, the scientific community has focused considerable research efforts to understand the spread of the virus. Despite a tremendous volume of research in this area, the dynamics of the immune response to SARS-CoV-2 has been hampered due to limited analysis of the experimental or clinical information to date. Mathematical models that account for the interaction between SARS-CoV-2 and the human immune system will improve the scientific community’s ability to analyze the amount of data available.We develop a mathematical model for the immune response to SARS-CoV-2 to investigate the role of various pathways in successful viral clearance and the key mechanisms responsible for disease severity. These interactions are captured by a system of ordinary and delayed differential equations. We conduct parameter estimation based on experimental data and investigate model behaviors via computational simulations. Our model demonstrates key aspects of the immune response to SARS-CoV-2 which might be responsible for disease severity. Specifically, Natural Killer Cell dysfunction impairs its ability to eliminate infected cells effectively. This could be used to serve as a foundation for the development of therapeutic strategies.

Authors: Hwayeon Ryu, Ayesh Awad, Keopagnapech Ngoun, Murilo Ferreira Lopes, Nicolas Alvarez