Stochastic simulation and the detection of immunity to schistosome infections

In this paper we address the question of detecting immunity to helminth inf ections from patterns of infection in endemic communities. We use stochasti c simulations to investigate whether it would be possible to detect pattern s predicted by theoretical models, using typical field data. Thus, our tech nique is to simulate a theoretical model, to generate the data that would b e obtained in field surveys and then to analyse these data using methods us ually employed for field data. The general behaviour of the model, and in p articular the levels of variability of egg counts predicted, show that the model is capturing most of the variability present in field data. However, analysis of the data in detail suggests that detection of immunity patterns in real data may be very difficult even if the underlying patterns are pre sent. Analysis of a real data set does show patterns consistent with acquir ed immunity and the implications of this are discussed.