Branching process approximation to the initial stages of an epidemicprocess has been used since the 1950's as a technique for providing stochastic counterparts to deterministic epidemic threshold theorems.One way of describing the approximation is to construct both branching and epidemic processes on the same probability space, insuch a way that their paths coincide for as long as possible. Inthis paper, it is shown, in the context of a Markovian model of parasiticinfection, that coincidence can be achieved with asymptotically high probability until MN infections have occurred, as long asMN = o(N 2/3), where N denotes the total number of hosts.