Transition from time-variant to static networks: Timescale separation in N -intertwined mean-field approximation of susceptible-infectious-susceptible epidemics

Robin Persoons*, Mattia Sensi, Bastian Prasse, Piet Van Mieghem

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

We extend the N-intertwined mean-field approximation (NIMFA) for the susceptible-infectious-susceptible (SIS) epidemiological process to time-varying networks. Processes on time-varying networks are often analyzed under the assumption that the process and network evolution happen on different timescales. This approximation is called timescale separation. We investigate timescale separation between disease spreading and topology updates of the network. We introduce the transition times T(r) and T¯(r) as the boundaries between the intermediate regime and the annealed (fast changing network) and quenched (static network) regimes, respectively, for a fixed accuracy tolerance r. By analyzing the convergence of static NIMFA processes, we analytically derive upper and lower bounds for T¯(r). Our results provide insights and bounds on the time of convergence to the steady state of the static NIMFA SIS process. We show that, under our assumptions, the upper-transition time T¯(r) is almost entirely determined by the basic reproduction number R0 of the network. The value of the upper-transition time T¯(r) around the epidemic threshold is large, which agrees with the current understanding that some real-world epidemics cannot be approximated with the aforementioned timescale separation.

Original languageEnglish
Article number034308
Number of pages19
JournalPhysical Review E
Volume109
Issue number3
DOIs
Publication statusPublished - 2024

Bibliographical note

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