1 Citation (Scopus)

Abstract

We study the dynamics of secondary infections on networks, in which only the individuals currently carrying a certain primary infection are susceptible to the secondary infection. In the limit of large sparse networks, the model is mapped to a branching process spreading in a random time-sensitive environment, determined by the dynamics of the underlying primary infection. When both epidemics follow the Susceptible-Infective-Recovered model, we show that in order to survive, it is necessary for the secondary infection to evolve on a timescale that is closely matched to that of the primary infection on which it depends.

Original languageEnglish
Pages (from-to)1122-1135
Number of pages14
JournalJournal of Statistical Physics
Volume171
Issue number6
Early online date26 Apr 2018
DOIs
Publication statusPublished - 1 Jun 2018

Keywords

  • Branching processes
  • Epidemics
  • Networks
  • SIR model
  • Superinfection

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics

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