Liu, Quan-Hui, Xinyue, Xiong, Zhang, Qian and Perra, Nicola ORCID: 0000-0002-5559-3064 (2018) Epidemic spreading on time-varying multiplex networks. Physical Review E, 98 (6). ISSN 2470-0053 (Print), 2470-0053 (Online) (doi:https://doi.org/10.1103/PhysRevE.98.062303)

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Abstract

Social interactions are stratified in multiple contexts and are subject to complex temporal dynamics. The systematic study of these two features of social systems has started only very recently, mainly thanks to the development of multiplex and time-varying networks. However, these two advancements have progressed almost in parallel with very little overlap. Thus, the interplay between multiplexity and the temporal nature of connectivity patterns is poorly understood. Here, we aim to tackle this limitation by introducing a time-varying model of multiplex networks. We are interested in characterizing how these two properties affect contagion processes. To this end, we study SIS epidemic models unfolding at comparable time-scale respect to the evolution of the multiplex network. We study both analytically and numerically the epidemic threshold as a function of the multiplexity and the features of each layer. We found that, higher values of multiplexity significantly reduce the epidemic threshold especially when the temporal activation patterns of nodes present on multiple layers are positively correlated. Furthermore, when the average connectivity across layers is very different, the contagion dynamics are driven by the features of the more densely connected layer. Here, the epidemic threshold is equivalent to that of a single layered graph and the impact of the disease, in the layer driving the contagion, is independent of the multiplexity. However, this is not the case in the other layers where the spreading dynamics are sharply influenced by it. The results presented provide another step towards the characterization of the properties of real networks and their effects on contagion phenomena.

Item Type:	Article
Uncontrolled Keywords:	Multiplex Networks, Epidemic Spreading on Networks
Subjects:	H Social Sciences > HB Economic Theory
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Networks and Urban Systems Centre (NUSC) > Centre for Business Network Analysis (CBNA) Faculty of Business > Department of International Business & Economics
Last Modified:	21 Oct 2020 10:05
URI:	http://gala.gre.ac.uk/id/eprint/22197

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