title: Global efficiency of local immunization on complex networks.
abstract: Epidemics occur in all shapes and forms: infections propagating in our sparse sexual networks, rumours and diseases spreading through our much denser social interactions, or viruses circulating on the Internet. With the advent of large databases and efficient analysis algorithms, these processes can be better predicted and controlled. In this study, we use different characteristics of network organization to identify the influential spreaders in 17 empirical networks of diverse nature using 2 epidemic models. We find that a judicious choice of local measures, based either on the network's connectivity at a microscopic scale or on its community structure at a mesoscopic scale, compares favorably to global measures, such as betweenness centrality, in terms of efficiency, practicality and robustness. We also develop an analytical framework that highlights a transition in the characteristic scale of different epidemic regimes. This allows to decide which local measure should govern immunization in a given scenario.
authors.affiliation: Département de Physique, de Génie Physique, et d'Optique, Université Laval, Québec (Québec), Canada G1V 0A6.
authors.forename: Laurent
authors.initials: L
authors.lastname: Hébert-Dufresne
authors.forename: Antoine
authors.initials: A
authors.lastname: Allard
authors.forename: Jean-Gabriel
authors.initials: JG
authors.lastname: Young
authors.forename: Louis J
authors.initials: LJ
authors.lastname: Dubé
mesh_terms: D000465:Algorithms; D004196:Disease Outbreaks / Q000517:prevention & control*; D006801:Humans; D007114:Immunization; D020407:Internet