Infection-Probability-Dependent Interlayer Interaction Propagation Processes in Multiplex Networks

Abstract

Different spreading processes in multiplex networks may interact with each other and display intertwined effects. In this paper, we propose a theoretical framework called infection-probability-dependent interlayer interaction propagation processes in multiplex networks with an arbitrary number of layers, to more precisely depict the intertwined effects which bring challenges to the existing state-dependent interlayer interaction models. Specifically, the spreading rate of each node is regulated by the proposed spreading rate function (SRF) which depends on both the intrinsic dynamics in its layer and the infection probabilities of its counterparts. We propose an algorithm to obtain the spreading threshold of each layer of the proposed theoretical framework. We analyze the three-layer tuberculosis-awareness-flu model with the SRF of each node being the expectation of infection-probability-dependent spreading rate. This paper gives a thorough and detailed numerical investigation of the impact and interaction of system settings and the spreading threshold of each layer. We find that for tuberculosis spreading which is in competing relation with awareness and cooperation relation with flu, the epidemic threshold is a constant when other layers' intrinsic spreading rates are small. The cooperation layer has dramatic influence on the constant while the competing layer has no effect on it.