Predict the Transport, Deposition, and Infection of Inhaled SARS-CoV-2 Laden Droplets in Disease-specific Human Respiratory System using Computational Fluid-Particle Dynamics

Transmission-blocking interventions are a critical modality in the control of SARS-CoV-2, which needs a thorough understanding of the infection risks associated with different exposure conditions. However, fundamental understanding of the connections remains deficient among the SARS-CoV-2 laden aerosol airborne transmission, pulmonary transport, and infection, associated with different emission activities such as cough, sneeze, and talk. Limited by the operational flexibility and imaging resolution, in vitro and in vivo studies could not provide insights on the above-mentioned problem. To address the knowledge gap, our established Computational Fluid-Particle Dynamics (CFPD) model with the elastic whole lung has been proved to be a promising alternative in silico tool, along with our research experience in lung aerosol dynamics simulations focusing on COVID-19. Thus, the scientific goal of the project is to accurately predict the chain of events associated with SARS-CoV-2 laden aerosol droplets transmission, including (1) emission in exhalation clouds that propel SARS-CoV-2 laden droplets, (2) the rapid evolution of the droplets subject to different environmental factors (including moisture and, temperature), (3) inhalation and rehydration in pulmonary routes, and (4) the host cell dynamics after their deposition in the lung. Employing our established CFPD and virtual lung model in Ansys Fluent, we propose two specific objectives over a 6-month research period (see Fig. 1):\n Objective 1 (Month 1-3): Simulate the transport, deposition, and infection of inhaled SARS-CoV-2 laden droplets in a static whole-lung model without airway deformation associated with different emission activities. At the end of Objective 1, it is expected that the lung aerosol dynamics results can provide insights into the infection risks related to different human activities and the recommendations on the mitigation plan to reduce the infection risks.\n\nObjective 2 (Month 4-6): Employ our elastic whole-lung model and simulate the transport, deposition, and infection of inhaled SARS-CoV-2 laden droplets with disease-specific airway deformation kinematics. At the end of this, the simulation results will provide insights into the differences in SARS-CoV-2 transport and infection in between healthy lung and lung with underlying conditions, thereby shedding lights on understanding the disease-specific immune system responses to the deposition of SARS-CoV-2 laden droplets in human respiratory systems. \n\nTo further account for the inter-subject variability, we will also construct a virtual population group of patients with COPD using open-access CT/MRI image libraries, and simulate and investigate the anatomical variability effect of the airway on SARS-CoV-2 transmission and infection. As one of the broader impacts, the proposed computational research and modeling framework can also be used for evaluating the effectiveness to treat COVID-19 via inhalation therapies, e.g., delivery of a nebulized mixture of interferon- α (IFN-α) and sterile water for injection via mouth inhalation.