With the premise that social interactions are described by power-law
distributions, we study a SIR stochastic dynamic on a static scale-free random
network generated via configuration model. We verify our model with respect to
deterministic considerations and provide a theoretical result on the
probability of the extinction of the disease. Based on this calibration, we
explore the variability in disease spread by stochastic simulations. In
particular, we demonstrate how important epidemic indices change as a function
of the contagiousness of the disease and the connectivity of the network. Our
results quantify the role of starting node degree in determining these indices,
commonly used to describe epidemic spread.Comment: 22 pages, 9 figure