Abstract
We study the susceptible-infected model with power-law waiting time distributions , as a model of spreading dynamics under heterogeneous human activity patterns. We found that the average number of new infections at time decays as a power law in the long-time limit, , leading to extremely slow prevalence decay. We also found that the exponent in the spreading dynamics is related to that in the waiting time distribution in a way depending on the interactions between agents but insensitive to the network topology. These observations are well supported by both the theoretical predictions and the long prevalence decay time in real social spreading phenomena. Our results unify individual activity patterns with macroscopic collective dynamics at the network level.
- Received 16 June 2010
DOI:https://doi.org/10.1103/PhysRevE.83.036102
©2011 American Physical Society