Cargando…

Epidemics in Partially Overlapped Multiplex Networks

Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nod...

Descripción completa

Detalles Bibliográficos
Autores principales: Buono, Camila, Alvarez-Zuzek, Lucila G., Macri, Pablo A., Braunstein, Lidia A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3954885/
https://www.ncbi.nlm.nih.gov/pubmed/24632709
http://dx.doi.org/10.1371/journal.pone.0092200
Descripción
Sumario:Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction [Image: see text] of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted [Image: see text]. We also theoretically determine the dependence of the epidemic threshold on the fraction [Image: see text] of shared nodes in a system composed of two layers. We find that in the limit of [Image: see text] the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.