Cooperative epidemics on multiplex networks

Abstract

The spread of one disease, in some cases, can stimulate the spreading of another infectious disease. Here, we treat analytically a symmetric coinfection model for spreading of two diseases on a two-layer multiplex network. We allow layer overlapping, but we assume that each layer is random and locally loopless. Infection with one of the diseases increases the probability of getting infected with the other. Using the generating function method, we calculate exactly the fraction of individuals infected with both diseases (so-called coinfected clusters) in the stationary state, as well as the epidemic spreading thresholds and the phase diagram of the model.With increasing cooperation, we observe a tricritical point and the type of transition changes from continuous to hybrid. Finally, we compare the coinfected clusters in the case of cooperating diseases with the so-called "viable" clusters in networks with dependencies.

7 pages, 7 figures

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• Multilayer Network Science: from Cells to Societies
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• Pattern dynamics of interacting contagions
• Competition between vaccination and disease spreading
• Competition, Collaboration, and Optimization in Multiple Interacting Spreading Processes
• Sudden spreading of infections in an epidemic model with a finite seed fraction
• Effect of network clustering on mutually cooperative coinfections
• Influence of Information Blocking on the Spread of Virus in Multilayer Networks
• Co-Contagion Diffusion on Multilayer Networks
• Optimal vaccination program for two infectious diseases with cross immunity
• Deep Learning Super-Diffusion in Multiplex Networks