The values of the parameters of our model can be estimated from empirical data. The relationship between the distance from a group's territory and the hotspot visitation rate can be estimated using capture-mark recapture and telemetric data, between-group contact rates can be estimated from direct observation or telemetric data, and plausible distributions of disease transmission rates can be found in the literature. The step length of the biased random walk is assumed to have a fixed value (here, 0.25 times the size of a territory). This parameter does not need to be estimated accurately since it is redundant with another parameter, the traveler-resident contact rate, which is allowed to vary. Thus, the model can be applied to a broad range of host-parasite systems, from primate groups travelling to waterholes on a daily basis [37, 38] to large mammals visiting every few weeks mineral-rich Figure 5 . Number of hotspots. Each line graphs the change in attack rate as a function of the number of hotspots, for a different value of P B (from 4e-04 to 16e-04). Results are presented for hotspots ranging from 1-100 (left) and 1-500 (right) in the Sick-stay model (top) and the Sick-travel model (bottom). Each value is averaged over 1000 stochastic simulations assuming R = 30, P w = 0.06, P T = 4e-04. Each hotspot was located randomly in the population, and disease was introduced into the group ranging in the middle of the habitat. doi:10.1371/journal.pone.0031290.g005 areas [12, 13, 39] . In our model, the impact of the hotspot is particularly sensitive to the ratio between the local and the traveler-resident between-group transmissions. When the local between-neighbour transmission is high compared to the travelerresident transmission, the impact of the hotspot is minimal.