Temporal interactions facilitate endemicity in the susceptible-infected-susceptible epidemic model

Leo Speidel, Konstantin Klemm, Víctor M. Eguíluz, Naoki Masuda

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Data of physical contacts and face-to-face communications suggest temporally varying networks as the media on which infections take place among humans and animals. Epidemic processes on temporal networks are complicated by complexity of both network structure and temporal dimensions. Theoretical approaches are much needed for identifying key factors that affect dynamics of epidemics. In particular, what factors make some temporal networks stronger media of infection than other temporal networks is under debate. We develop a theory to understand the susceptible-infected-susceptible epidemic model on arbitrary temporal networks, where each contact is used for a finite duration. We show that temporality of networks lessens the epidemic threshold such that infections persist more easily in temporal networks than in their static counterparts. We further show that the Lie commutator bracket of the adjacency matrices at different times is a key determinant of the epidemic threshold in temporal networks. The effect of temporality on the epidemic threshold, which depends on a data set, is approximately predicted by the magnitude of a commutator norm.

Original languageEnglish
Article number073013
JournalNew Journal of Physics
Volume18
Issue number7
DOIs
Publication statusPublished - Jul 2016

Keywords

  • SIS model
  • epidemic threshold
  • temporal networks

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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