title: Impacts of clustering on interacting epidemics.
abstract: Since community structures in real networks play a major role for the epidemic spread, we therefore explore two interacting diseases spreading in networks with community structures. As a network model with community structures, we propose a random clique network model composed of different orders of cliques. We further assume that each disease spreads only through one type of cliques; this assumption corresponds to the issue that two diseases spread inside communities and outside them. Considering the relationship between the susceptible-infected-recovered (SIR) model and the bond percolation theory, we apply this theory to clique random networks under the assumption that the occupation probability is clique-type dependent, which is consistent with the observation that infection rates inside a community and outside it are different, and obtain a number of statistical properties for this model. Two interacting diseases that compete the same hosts are also investigated, which leads to a natural generalization of analyzing an arbitrary number of infectious diseases. For two-disease dynamics, the clustering effect is hypersensitive to the cohesiveness and concentration of cliques; this illustrates the impacts of clustering and the composition of subgraphs in networks on epidemic behavior. The analysis of coexistence/bistability regions provides significant insight into the relationship between the network structure and the potential epidemic prevalence.
authors.affiliation: Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Tokyo 153-8505, Japan. bingbignmath@gmail.com
authors.forename: Bing
authors.initials: B
authors.lastname: Wang
authors.forename: Lang
authors.initials: L
authors.lastname: Cao
authors.forename: Hideyuki
authors.initials: H
authors.lastname: Suzuki
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
mesh_terms: D016000:Cluster Analysis; D060085:Coinfection / Q000453:epidemiology / Q000635:transmission; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission; D058872:Epidemics; D006801:Humans; D008954:Models, Biological; D049490:Systems Biology / Q000379:methods