Comparison of numerical results from temporal Gillespie and rejection sampling algorithms.

(A) Mean number of nodes in each state of the SIR model as function of time. (B) Distribution of final epidemic sizes (number of recovered nodes when I = 0) in the SIR model. (C) Mean number of nodes in each state of the SIS model as function of time. (D) Distribution of the number of infected nodes in the stationary state (t → ∞) of the SIS model. All simulations were performed 1 000 000 times with the root node chosen at random on an activity driven network [41] consisting of N = 100 nodes, with activities a_i = ηz_i, where η = 0.1 and $z_i\sim z_i^{-3.2}$ for z_i ∈ [0.03, 1), and a node formed two contacts when active. Parameters of the epidemic processes were βΔt = 10⁻² and μΔt = 10⁻⁴.