title: Adaptive networks: Coevolution of disease and topology.
abstract: Adaptive networks have been recently introduced in the context of disease propagation on complex networks. They account for the mutual interaction between the network topology and the states of the nodes. Until now, existing models have been analyzed using low complexity analytical formalisms, revealing nevertheless some novel dynamical features. However, current methods have failed to reproduce with accuracy the simultaneous time evolution of the disease and the underlying network topology. In the framework of the adaptive susceptible-infectious-susceptible (SIS) model of Gross [Phys. Rev. Lett. 96, 208701 (2006)]10.1103/PhysRevLett.96.208701, we introduce an improved compartmental formalism able to handle this coevolutionary task successfully. With this approach, we analyze the interplay and outcomes of both dynamical elements, process and structure, on adaptive networks featuring different degree distributions at the initial stage.
authors.affiliation: Département de Physique, de Génie Physique, et d'Optique, Université Laval, Québec, Québec, Canada G1V 0A6.
authors.forename: Vincent
authors.initials: V
authors.lastname: Marceau
authors.forename: Pierre-André
authors.initials: PA
authors.lastname: Noël
authors.forename: Laurent
authors.initials: L
authors.lastname: Hébert-Dufresne
authors.forename: Antoine
authors.initials: A
authors.lastname: Allard
authors.forename: Louis J
authors.initials: LJ
authors.lastname: Dubé
mesh_terms: D004194:Disease; D004198:Disease Susceptibility; D018562:Disease Transmission, Infectious; D058872:Epidemics; D008954:Models, Biological; D015995:Prevalence; D013997:Time Factors