Modeling two competing infectious diseases in a metropolitan contact network

Infectious diseases rarely spread in isolation, and the competing spreading of multiple diseases widely exists. However, existing studies on the dynamics of competing infectious diseases typically rely on networked populations, lacking systematic research on specific metropolitan areas. This study proposes a competing infectious disease model to describe two competing infectious diseases spreading in metropolitan areas. An analytical framework of the theory is first developed to characterize this high-dimension system though expanded mean-field theory. To describe this spreading process more conveniently, we propose a dimension-reduction method to reduce the system complexity. Finally, we use an age-contact data-driven approach to simulate the spreading of two competing infectious diseases in metropolitan cities like New York. The results validate our dimension-reduction method’s reliability, allowing us to describe the high-dimension system through a one-dimensional equation. We observed three main scenarios of competing disease spreading, i.e., neither disease can break out, one disease dominates, while the other is suppressed, and the two diseases coexist throughout the spreading. Moreover, our simulations show that the workplace favours specific diseases with stronger spreading capabilities than other settings.