Ranking of Nodal Infection Probability in Susceptible-Infected-Susceptible Epidemic

Bo Qu, Cong Li*, Piet Van Mieghem, Huijuan Wang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)
46 Downloads (Pure)

Abstract

The prevalence, which is the average fraction of infected nodes, has been studied to evaluate the robustness of a network subject to the spread of epidemics. We explore the vulnerability (infection probability) of each node in the metastable state with a given effective infection rate τ. Specifically, we investigate the ranking of the nodal vulnerability subject to a susceptible-infected-susceptible epidemic, motivated by the fact that the ranking can be crucial for a network operator to assess which nodes are more vulnerable. Via both theoretical and numerical approaches, we unveil that the ranking of nodal vulnerability tends to change more significantly as τ varies when τ is smaller or in Barabási-Albert than Erdos-Rényi random graphs.

Original languageEnglish
Article number9233
Pages (from-to)1-10
Number of pages10
JournalScientific Reports
Volume7
DOIs
Publication statusPublished - 2017

Keywords

  • Complex networks
  • Statistical physics

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