title: Suppressing traffic-driven epidemic spreading by edge-removal strategies.
abstract: The interplay between traffic dynamics and epidemic spreading on complex networks has received increasing attention in recent years. However, the control of traffic-driven epidemic spreading remains to be a challenging problem. In this Brief Report, we propose a method to suppress traffic-driven epidemic outbreak by properly removing some edges in a network. We find that the epidemic threshold can be enhanced by the targeted cutting of links among large-degree nodes or edges with the largest algorithmic betweenness. In contrast, the epidemic threshold will be reduced by the random edge removal. These findings are robust with respect to traffic-flow conditions, network structures, and routing strategies. Moreover, we find that the shutdown of targeted edges can effectively release traffic load passing through large-degree nodes, rendering a relatively low probability of infection to these nodes.
authors.affiliation: Department of Physics, Fuzhou University, Fuzhou 350108, China. hxyang01@gmail.com
authors.forename: Han-Xin
authors.initials: HX
authors.lastname: Yang
authors.forename: Zhi-Xi
authors.initials: ZX
authors.lastname: Wu
authors.forename: Bing-Hong
authors.initials: BH
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology*; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data*; D006801:Humans; D008962:Models, Theoretical