Co-evolution of two interacting epidemics driven by traffic flow in multiplex networks

Abstract While most studies on traffic-driven epidemic spreading in complex networks focus on single-pathogen scenarios, real-world transmission often involves interacting epidemics. To address this gap, we propose a novel model for the co-evolution of two interacting epidemics driven by traffic flow in multiplex networks. We systematically examine both the suppressive and enhancing effects that one epidemic (i.e epidemic A ) may exert on the other (i.e epidemic B). Our results show that when epidemic B has a low infection rate $\beta_B$ and rapidly vanishes, it does not affect the steady-state infection density $\rho_A(\infty)$ or the epidemic threshold $\beta_c^A$ of epidemic A. However, as $\beta_B$ increases and epidemic B persists, the interaction parameter $x_A$ plays a decisive role. As $x_A$ increases, $\beta_c^A$ decreases. For $x_A1$, epidemic B facilitates the spread of epidemic A, indicating cooperative amplification. For $x_A=1$, the two epidemics evolve independently. These asymmetric interactions can fundamentally reshape the intrinsic propagation dynamics of each disease. Numerical simulations and theoretical analysis consistently reveal complex emergent behaviors arising from such coupled spreading processes, offering a more realistic framework for understanding multi-pathogen transmission in networked populations.