Zhongzhi Zhang et al J. Stat. Mech. (2008) P09008 doi:10.1088/1742-5468/2008/09/P09008
Zhongzhi Zhang1,2, Shuigeng Zhou1,2, Tao Zou1,2 and Guisheng Chen3
Show affiliationsThe conventional wisdom is that scale-free networks are prone to epidemic propagation; in the paper we demonstrate that, on the contrary, 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 the bond percolation process. We establish the existence of non-zero 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.
E-print Number: 0804.3186
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Issue 09 (September 2008)
Received 3 August 2008, accepted for publication 25 August 2008
Published 25 September 2008
Zhongzhi Zhang et al J. Stat. Mech. (2008) P09008
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