Fractal scale-free networks resistant to disease spread

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dc.creatorZhang, Zhongzhi
dc.creatorZhou, Shuigeng
dc.creatorTao, Zou
dc.creatorChen, Guisheng
dc.date2008-04-20
dc.date.accessioned2026-07-07T10:04:48Z
dc.date.available2026-07-07T10:04:48Z
dc.descriptionIn contrast to the conventional wisdom that scale-free networks are prone to epidemic propagation, in the paper we present that disease spreading is inhibited in fractal scale-free networks. We first propose a novel network model and show that it simultaneously has the following rich topological properties: scale-free degree distribution, tunable clustering coefficient, "large-world" behavior, and fractal scaling. Existing network models do not display these characteristics. Then, we investigate the susceptible-infected-removed (SIR) model of the propagation of diseases in our fractal scale-free networks by mapping it to bond percolation process. We find an existence of nonzero tunable epidemic thresholds by making use of the renormalization group technique, which implies that power-law degree distribution does not suffice to characterize the epidemic dynamics on top of scale-free networks. We argue that the epidemic dynamics are determined by the topological properties, especially the fractality and its accompanying "large-world" behavior.
dc.description13 pages, 4 figures
dc.identifierhttps://arxiv.org/abs/0804.3186
dc.identifierhttp://arxiv.org/abs/0804.3186
dc.identifierJournal of Statistical Mechanics: Theory and Experiment, 2008, P09008.
dc.identifierdoi:10.1088/1742-5468/2008/09/P09008
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/169810
dc.subjectPopulations and Evolution
dc.subjectStatistical Mechanics
dc.titleFractal scale-free networks resistant to disease spread
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