title: Competitive epidemic spreading over arbitrary multilayer networks.
abstract: This study extends the Susceptible-Infected-Susceptible (SIS) epidemic model for single-virus propagation over an arbitrary graph to an Susceptible-Infected by virus 1-Susceptible-Infected by virus 2-Susceptible (SI_{1}SI_{2}S) epidemic model of two exclusive, competitive viruses over a two-layer network with generic structure, where network layers represent the distinct transmission routes of the viruses. We find analytical expressions determining extinction, coexistence, and absolute dominance of the viruses after we introduce the concepts of survival threshold and absolute-dominance threshold. The main outcome of our analysis is the discovery and proof of a region for long-term coexistence of competitive viruses in nontrivial multilayer networks. We show coexistence is impossible if network layers are identical yet possible if network layers are distinct. Not only do we rigorously prove a region of coexistence, but we can quantitate it via interrelation of central nodes across the network layers. Little to no overlapping of the layers' central nodes is the key determinant of coexistence. For example, we show both analytically and numerically that positive correlation of network layers makes it difficult for a virus to survive, while in a network with negatively correlated layers, survival is easier, but total removal of the other virus is more difficult.
authors.affiliation: Electrical and Computer Engineering Department, Kansas State University, Manhattan, Kansas 66506, USA and and Institute of Computational Comparative Medicine, Kansas State University, Manhattan, Kansas 66506, USA.
authors.forename: Faryad
authors.initials: F
authors.lastname: Darabi Sahneh
authors.affiliation: Electrical and Computer Engineering Department, Kansas State University, Manhattan, Kansas 66506, USA and and Institute of Computational Comparative Medicine, Kansas State University, Manhattan, Kansas 66506, USA.
authors.forename: Caterina
authors.initials: C
authors.lastname: Scoglio
mesh_terms: D003198:Computer Simulation; D004198:Disease Susceptibility; D018562:Disease Transmission, Infectious; D008954:Models, Biological; D013269:Stochastic Processes; D014777:Virus Diseases / Q000453:epidemiology*; D018406:Virus Physiological Phenomena