Impacts of clustering on interacting epidemics

Journal of Theoretical Biology
Bing WangKazuyuki Aihara

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 ...Continue Reading

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Citations

Apr 2, 2016·Bulletin of Mathematical Biology·Ágnes BodóPéter L Simon
May 30, 2014·Scientific Reports·Wei WangGyuWon Lee
Jun 13, 2015·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Carlos P Herrero
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Jan 24, 2015·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Yong MinXiaogang Jin
Jan 14, 2018·Mathematical Biosciences·Jinxian LiZhen Jin
Jul 18, 2021·Physical Review. E·Peter MannSimon Dobson

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