The present paper describes how age–intensity profiles of macroparasite burdens are affected by processes underlying the distribution of the parasite numbers in host populations. In a comparative way, we consider the following 6 processes: (i) age-dependent exposure, (ii) parasite-induced host mortality, (iii) heterogeneity within the host population, (iv) clumped infection, (v) density-dependent parasite mortality and (vi) density-dependent parasite establishment. For each of these processes, we show typical patterns in the age–intensity profile and provide, if possible, explicit and simple solutions for the age-dependent mean parasite burden and the corresponding dispersion patterns. Emphasis is given to density-dependent parasite establishment and to age–intensity profiles resulting from the superposition of different processes. By means of 2 examples we show that the interpretation of observed patterns can be ambiguous if more than 1 process takes place. These findings underline that age–intensity profiles should be interpreted on the basis of available a priori knowledge about the processes assumed to be involved. For purposes of testing different hypotheses, a simulation program is provided with which discrepancies between model prediction and data can be explored.

This note gives the rate for a Wasserstein distance between the distribution of a Bernoulli process on discrete time and that of a Poisson process, using Stein's method and Palm theory. The result here highlights the possibility that the logarithmic factor involved in the upper bounds established by Barbour and Brown (1992) and Barbour et al. (1995) may be superfluous in the true Wasserstein distance between the distributions of a point process and a Poisson process.