  We study the effect of heterogeneous temporal activations on epidemic
spreading in temporal networks. We focus on the
susceptible-infected-susceptible (SIS) model on activity-driven networks with
burstiness. By using an activity-based mean-field approach, we derive a closed
analytical form for the epidemic threshold for arbitrary activity and
inter-event time distributions. We show that, as expected, burstiness lowers
the epidemic threshold while its effect on prevalence is twofold. In
low-infective systems burstiness raises the average infection probability,
while it weakens epidemic spreading for high infectivity. Our results can help
clarify the conflicting effects of burstiness reported in the literature. We
also discuss the scaling properties at the transition, showing that they are
not affected by burstiness.
