SIR Epidemics in Interconnected Networks: threshold curve and phase transition

Abstract: To simplify mathematical models of disease spread, we often assume equal contact rates among hosts, but real-world scenarios differ. Network-based frameworks help capture these complexities and structural variations in actual systems. We explore two scenarios involving Susceptible-Infected-Recovered (SIR) dynamics in interconnected networks. First, we study how the epidemic threshold of a contact network changes when coupled with another network, holding infection strength constant. Our model treats both contact networks and interconnections generically. We depict the epidemic threshold curve for interconnected networks, accounting for initial infection in either or both networks. If normalized infection strengths surpass this threshold curve, the disease spreads; below it, it does not, regardless of interconnection level. In the second scenario, we investigate disease spillover, where a novel host population network is affected by a reservoir network. A clear phase transition occurs when the number of links or inter-network infection rate exceeds a threshold while other parameters remain fixed. Spillover exhibits two regimes: major and minor, based on interpopulation links and inter-network infection strength. High spillover probability occurs in the major region and low in the minor. The threshold link count varies with network topology for similar infected numbers in the reservoir network. In sum, our work enhances understanding of SIR dynamics in interconnected networks, offering insights into epidemic behavior in complex systems.