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

Journal Article (2017)
Author(s)

B Qu (TU Delft - Multimedia Computing)

C Li (Fudan University)

Piet Van Mieghem (TU Delft - Network Architectures and Services)

H. Wang (TU Delft - Multimedia Computing)

Copyright
© 2017 B. Qu, C. Li, P.F.A. Van Mieghem, H. Wang
DOI related publication
https://doi.org/10.1038/s41598-017-08611-9
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 B. Qu, C. Li, P.F.A. Van Mieghem, H. Wang
Volume number
7
Pages (from-to)
1-10
Reuse Rights

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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.