Network localization is unalterable by infections in bursts

Qiang Liu, Piet Van Mieghem

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
38 Downloads (Pure)


To shed light on the disease localization phenomenon, we study a bursty susceptible-infected-susceptible (SIS) model and analyze the model under the mean-field approximation. In the bursty SIS model, the infected nodes infect all their neighbors periodically, and the near-threshold steady-state prevalence is non-constant and maximized by a factor equal to the largest eigenvalue λ1 of the adjacency matrix of the network. We show that the maximum near-threshold prevalence of the bursty SIS process on a localized network tends to zero even if λ1 diverges in the thermodynamic limit, which indicates that the burst of infection cannot turn a localized spreading into a delocalized spreading. Our result is evaluated both on synthetic and real networks.
Original languageEnglish
Pages (from-to)983 - 989
Number of pages7
JournalIEEE Transactions on Network Science and Engineering
Issue number4
Publication statusPublished - 24 Dec 2018

Bibliographical note

Accepted author manuscript


  • Complex networks
  • localization
  • epidemic process
  • susceptible-infected-susceptible model


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  • Spreading on Networks

    Liu, Q., 2019, Delft. 142 p.

    Research output: ThesisDissertation (TU Delft)

    Open Access
    140 Downloads (Pure)

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