Viewing the transmission dynamics as a discrete time stochastic process rather than a deterministic system of coupled differential equations implies a distribution of possible outcomes for the epidemic. By conditioning on parameter values and initial conditions (S 0~7 62, I 0~1 ), Monte Carlo simulation can be used to explore the distributions of numbers of susceptible, infected, and recovered individuals, as well as total accrued cost, as functions of time. Murray provides estimates of the transmission rate (b b~0:00218) and recovery rate (v v~0:4), which we regard as the ''true'' underlying parameter values in our simulations. Additional aspects of the transmission function are discussed in the Methods section. We assume that all costs can be expressed in a common monetary cost unit. Other choices of cost functions that address the issue of nonconformable costs (e.g. lives vs dollars) are mentioned in the Discussion.