In general, these individual-based models have properties in common with both continuous space models and stochastic metapopulation models; a transmission kernel is generally used to capture the spatial spread of infection but this is tempered by the stochastic, individual-based nature of the population processes leading to a slower rate of spatial spread (Lewis 2000). Here, as an example of this methodology, we will formulate a general stochastic individual-based model where each host is capable of localized movement and transmission is distance dependent; this gives rise to five distinct probabilistic events: transmission, recovery, birth, death, and movement. Transmission. Transmission is captured using a technique similar to the integro-differential equations models. The rate of transmission (or force of infection) to a susceptible
individual, i, is given by: