Dynamics of epidemic diseases on a growing adaptive network

Guven Demirel , Edmund Barter, Thilo Gross

Research output: Contribution to journalArticle (Academic Journal)peer-review

16 Citations (Scopus)
233 Downloads (Pure)

Abstract

The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists
Original languageEnglish
Article number42352
Number of pages15
JournalScientific Reports
Volume7
DOIs
Publication statusPublished - 10 Feb 2017

Keywords

  • Applied mathematics
  • Complex network

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