For our baseline network parameters, we set n~4 to determine the effects of finite neighbourhood size and clustering. We also take the network size to be N~10 5 to produce little variability due to stochastic effects after the initial stages of an epidemic. Our main aim is to measure the effects of clustering, w, and this is varied between 0 and 0:5. The recovery rate, g, can be formally set to 1 through non-dimensionalisation, and we set g T~1 0 3 to achieve separation of timescales. Our epidemiological motivation for this separation is the expected difference in the time from infection to detection and treatment, and the time taken to notify sexual partners. For emerging respiratory infections, such a separation of timescales would, of course, not exist.