Modeling and Simulation of the SARS-COV-2 Lung Infection and Immune Response with Cell-DEVS

Understanding why patients’ viral loads vary dramatically across individuals is a critical challenge in addressing respiratory infections, especially the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spatial-temporal dynamics of viral infection in the respiratory system and the immune system’s response remain difficult to study. Using modelling and simulation (M&S) techniques may address this problem. In this paper, we present a novel modelling approach using the Cell-DEVS formalism (a combination of Cellular Automata and DEVS), to simulate the spatial-temporal dynamics of viral spread in the lungs. Using a two-dimensional cellular space that mimics a lung, the proposed approach focuses also on the immune system response, viral infection spread, state of lung epithelial tissue damage, and immune cells’ state. We demonstrate the pertinence of our proposal on three different scenarios representing three types of patients. Qualitative evaluation by expert biologists confirms that the produced simulations match the observations made on patients.