After generating the infection network, we simulate S susceptible-infected-recovered (SIR) epidemics. To start the epidemic, we initialize the network so that all nodes are susceptible. One random node is then infected to act as seed of the epidemic. At each time step, every infected node will transmit the disease to its susceptible neighbours with probability q. After a certain time interval t R , the infected nodes will recover and become immune to subsequent infections. This way, the number of infected nodes grows from the single seed, peaks, and thereafter decreases as more and more nodes recover and become immune. When there are no more infected nodes in the network, the epidemic ends and all nodes are reset to the susceptible state for simulating the next epidemic.