Abstract
We extend the -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 and as the boundaries between the intermediate regime and the annealed (fast changing network) and quenched (static network) regimes, respectively, for a fixed accuracy tolerance . By analyzing the convergence of static NIMFA processes, we analytically derive upper and lower bounds for . 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 is almost entirely determined by the basic reproduction number of the network. The value of the upper-transition time 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.
6 More- Received 3 November 2023
- Accepted 15 February 2024
- Corrected 3 April 2024
DOI:https://doi.org/10.1103/PhysRevE.109.034308
©2024 American Physical Society
Physics Subject Headings (PhySH)
Corrections
3 April 2024
Correction: The affiliation indicators for the second, third, and last authors were not ascribed properly during the production cycle and have been corrected.