Speaker
Description
Respiratory viruses, such as influenza and SARS-CoV-2, pose significant global health threats. Mathematical models have been instrumental in understanding epidemiological spread and within-host viral dynamics. These are typically compartmental models that neglect spatial structure. In contrast, agent-based models (ABMs) enable the representation of localized, single-cell interactions and spatial structure within infected tissues. We developed a multiscale, spatial agent-based model in PhysiCell to investigate viral spread and immune dynamics within the lungs following influenza infection. In our model, cells are represented as off-lattice agents capable of migrating, proliferating, and exchanging substrates within the microenvironment. Viral propagation
and immune interactions are resolved at single-cell resolution, with diffusive transport coupled through BioFVM. We coupled viral dynamics to the spatiotemporal dynamics of immune cells, including macrophages, neutrophils, CD8+ and CD4+ T cells, dendritic cells, and key inflammatory mediators (i.e., cytokines, chemokines, IFN, ROS), to
quantify infection control and tissue damage. Using this framework, we characterized how inhaled virus spreads within lung tissue and how immune responses shape spatial infection patterns. By integrating spatial structure and cellular-level interactions within a
multiscale ABM framework, this work advances mechanistic understanding of within-host viral dynamics. Overall, spatially resolved modeling provides a computational platform for dissecting infection control mechanisms and supporting preparedness against emerging respiratory viruses, with potential applications in the pre-clinical
evaluation of therapeutic strategies.
