Bacteriophages are viruses that infect bacteria and represent a promising strategy to fight antibiotic-resistant pathogens. Unfortunately, the understanding on how phages interact with bacteria in mucus—a substance which coats the organs in many living systems—is limited and experimentally challenging. Recent laboratory experiments have revealed T4 phage capsids have Hoc proteins which interact with the mucin network and has been correlated with an enhancement of phage infectivity. The goal of our research is to develop a computational framework to advance the understanding of phage-bacteria infection dynamics in the mucus environment, providing a rapid and systematic platform to screen for ideal viruses for pathogen control. Using an agent based framework—we investigate the mechanisms that govern the existence of T4 bacteriophage among its natural host, Escherichia coli, while suspended in mucus. For the project, we developed and calibrated an agent based phage-bacteria-mucus system which encompasses various microbial and mucus parameters. The motion of T4 phage is captured using a continuous time random walk which recovers the subdiffusion of T4 due to the interaction of Hoc proteins with mucus. The motion of E. coli is modeled to reproduce the characteristic run-and-tumble stages. The mucus environment is modeled by incorporating various concentration profiles. Our model is calibrated and tested using empirical data obtained from the Viral Information Institute at San Diego State University. We find phage-bacteria ecosystem dynamics in mucus are highly dependent on the mucus concentration and lifestyle characteristics of each species. Using both numerical and analytical techniques, we demonstrate how under certain conditions, the properties of either bacteriophage, bacteria or mucus can massively affect the existence, coexistence or extinction of the phage-bacteria ecosystem.