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Epidemic spreading driven by biased random walks

Author

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  • Pu, Cunlai
  • Li, Siyuan
  • Yang, Jian

Abstract

Random walk is one of the basic mechanisms of many network-related applications. In this paper, we study the dynamics of epidemic spreading driven by biased random walks in complex networks. In our epidemic model, infected nodes send out infection packets by biased random walks to their neighbor nodes, and this causes the infection of susceptible nodes that receive the packets. Infected nodes recover from the infection at a constant rate λ, and will not be infected again after recovery. We obtain the largest instantaneous number of infected nodes and the largest number of ever-infected nodes respectively, by tuning the parameter α of the biased random walks. Simulation results on model and real-world networks show that spread of the epidemic becomes intense and widespread with increase of either delivery capacity of infected nodes, average node degree, or homogeneity of node degree distribution.

Suggested Citation

  • Pu, Cunlai & Li, Siyuan & Yang, Jian, 2015. "Epidemic spreading driven by biased random walks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 230-239.
    • Handle: RePEc:eee:phsmap:v:432:y:2015:i:c:p:230-239
    DOI: 10.1016/j.physa.2015.03.035
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    Citations

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    Cited by:

    1. Kabir, K.M. Ariful & Tanimoto, Jun, 2019. "Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 41-55.
    2. Schaum, Alexander & Bernal Jaquez, Roberto, 2016. "Estimating the state probability distribution for epidemic spreading in complex networks," Applied Mathematics and Computation, Elsevier, vol. 291(C), pages 197-206.
    3. Wijesundera, Isuri & Halgamuge, Malka N. & Nirmalathas, Ampalavanapillai & Nanayakkara, Thrishantha, 2016. "MFPT calculation for random walks in inhomogeneous networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 986-1002.

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