In Silico Modeling of Virus Particle Propagation and Infectivity along the Respiratory Tract: A Case Study for SARS-COV-2

Respiratory viruses including Respiratory syncytial virus (RSV), influenza virus and cornaviruses such as Middle Eastern respiratory virus (MERS) and SARS-CoV-2 infect and cause serious and sometimes fatal disease in thousands of people annually. It is critical to understand virus propagation dynamics within the respiratory system because new insights will increase our understanding of virus pathogenesis and enable infection patterns to be more predictable in vivo, which will enhance targeting of vaccines and drug delivery. This study presents a computational model of virus propagation within the respiratory tract network. The model includes the generation network branch structure of the respiratory tract, biophysical and infectivity properties of the virus, as well as air flow models that aid the circulation of the virus particles. The model can also consider the impact of the immune response aim to inhibit virus replication and spread. The model was applied to the SARS-CoV-2 virus by integrating data on its life-cycle, as well as density of Angiotensin Converting Enzyme (ACE2) expressing cells along the respiratory tract network. Using physiological data associated with the respiratory rate and virus load that is inhaled, the model can improve our understanding of the concentration and spatiotemporal dynamics of virus.