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An alternative approach to characterize the topology of complex networks and its application in epidemic spreading

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Abstract

Based on the mean-field approach, epidemic spreading has been well studied. However, the mean-field approach cannot show the detailed contagion process, which is important in the control of epidemic. To fill this gap, we present a novel approach to study how the topological structure of complex network influences the concrete process of epidemic spreading. After transforming the network structure into hierarchical layers, we introduce a set of new parameters, i.e., the average fractions of degree for outgoing, ingoing, and remaining in the same layer, to describe the infection process. We find that this set of parameters are closely related to the degree distribution and the clustering coefficient but are more convenient than them in describing the process of epidemic spreading. Moreover, we find that the networks with exponential distribution have slower spreading speed than the networks with power-law degree distribution. Numerical simulations have confirmed the theoretical predictions.

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Authors and Affiliations

  1. Institute of Theoretical Physics and Department of Physics, East China Normal University, Shanghai, 200062, China

    Zonghua Liu & Xiaoyan Wu

  2. Department of Physics, The Chinese University of Hong Kong, Hong Kong, China

    Pak-Ming Hui

Authors
  1. Zonghua Liu
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  2. Xiaoyan Wu
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  3. Pak-Ming Hui
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Correspondence to Zonghua Liu.

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Liu, Z., Wu, X. & Hui, PM. An alternative approach to characterize the topology of complex networks and its application in epidemic spreading. Front. Comput. Sci. China 3, 324–334 (2009). https://doi.org/10.1007/s11704-009-0058-7

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  • DOI: https://doi.org/10.1007/s11704-009-0058-7

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