Dynamic models which predict changes in the intensity of schistosome infection with host age are fitted to pre-intervention Schistosoma mansoni data from Kenya. Age-specific post-treatment-reinfection data are used to estimate the force of infection, thus enabling investigation of the rate of worm death. An empirical and statistical approach is taken to the model fitting: where possible, distributional properties and function relationships are obtained from the data rather than assumed from theory. Attempts are made to remove known sources of bias. Maximum likelihood techniques, employed to allow for error in both the pre-intervention and reinfection data, yield confidence intervals for the worm life-span (CI95% = 5·7–10·5 years) and demonstrate that the worm death rate is unlikely to vary with host age. The possibilities and limitations of fitting dynamic models to data are discussed. We conclude that a detailed, quantitative approach will be necessary if progress is to be made with the interpretation of epidemiological data and the models intended to describe them.
