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The effect of acquired immunity on the duration of Plasmodium falciparum infections is unclear, although this is an important term in models of malaria transmission. It is problematical to determine the duration of infections because of the difficulty of distinguishing persisting infections from new ones, and because parasite densities are often transiently below the limit of detection. We recently developed a dynamic model for infection incidence, clearance and detection of multiple genotype P. falciparum infections and fitted it to a panel dataset from a longitudinal study in Northern Ghana. We now extend this model to allow for seasonal and age variation in infection rates and also age dependence in clearance and in detectability of infections. These models indicate that there is seasonal variation in the infection rate, and age dependence in detectability. The best fitting models had no age dependence in infection or clearance rates, suggesting that acquired immunity mainly affects detectability.

A discrete-time age-stage model is proposed for estimating the number of sequestered parasites in severe malaria patients. A Bayesian Markov chain Monte Carlo (MCMC) approach is used to model the dynamics of Plasmodium falciparum parasitaemia in 107 paediatric patients in a randomized controlled trial of quinine and artemether in Kenya, in whom 4-hourly peripheral parasitaemia determinations were made. The MCMC approach allows the model to be fitted simultaneously to the entire dataset, providing point and interval estimates for both population and individual patient parameters. Analysis of a simulated dataset indicated that the models gave good estimates of the distribution of parasites between different stages on enrolment, for patients with a wide range of initial states. The analysis of the Kenyan patients suggested that there is considerable variation between patients within the same centre, in both the proportion of sequestered parasites and the intrinsic rate of increase of the parasite population in the absence of treatment. The resulting models should prove a useful tool for cross-validating biochemical approaches for estimating the sequestered load.

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.

A model is presented which describes the aggregation of female Onchocerca volvulus in nodules and their distribution in the human population. The basic model is based on a single parameter, the formation probability q, which represents the probability with which incoming larvae form a new nodule. This parameter describes parasite behaviour which cannot easily be recognized in available data without modelling. The estimate for the average formation probability of muq = 0.39 suggests an attraction of the invading infective larvae to already existing nodules or resident worms with probability 0.61. No significant difference in muq was found between the forest and savanna parasite strains. The model can be used inversely to estimate the worm burden of persons from palpation data. The observed variance in the number of nodules per person requires the assumption of a variance-increasing mechanism which was implemented by heterogeneity within the host population (extended model with 2 parameters). Possible reasons for this heterogeneity are presented and its implications concerning the reproductive biology of the parasite are discussed.

A new mathematical model of Plasmodium falciparum asexual parasitaemia is formulated and fitted to 35 malaria therapy cases making a spontaneous recovery after primary inoculation. Observed and simulated case-histories are compared with respect to 9 descriptive statistics. The simulated courses of parasitaemia are more realistic than any previously published. The model uses a discrete time-step of 2 days. Its realistic behaviour was achieved by the following combination of features (i) intra-clonal antigenic variation, (ii) large variations of the variants' baseline growth rate, depending on both variant and case, (iii) innate autoregulation of the asexual parasite density, variable among cases, (iv) acquired variant-specific immunity and (v) acquired variant-transcending immunity, variable among cases. Aspects of the model's internal behaviour, concerning variant dynamics, as well as the respective contributions of the three control mechanisms (iii) - (v), are displayed. Some implications for pathogenesis and control are discussed.

We review the theoretical framework for exploring the impact of individual and spatial heterogeneities in patterns of exposure and contamination and on the basic reproduction number, R0, for human schistosomes. Analysis of water contact data for 5 communities in Zimbabwe and Mali suggests that the impact is substantial, increasing R0 by factors of up to 6.5, mostly due to highly overdispersed distributions of contact rates among individuals. Several practical conclusions emerge: concentration of contacts at a single site should be avoided; the impact of control targeted at certain sites cannot be predicted without knowledge of how individuals' contacts are distributed among sites; control programmes targeted at individuals or sites contributing most to transmission can be very efficient but, conversely, will be ineffective if any of these individuals or sites are missed.

The characteristically aggregated frequency distribution of macroparasites in their hosts is a key feature of host-parasite population biology. We begin with a brief review of the theoretical literature concerning parasite aggregation. Though this work has illustrated much about both the sources and impact of parasite aggregation, there is still no definite analysis of both these aspects. We then go on to illustrate the use of one approach to this problem--the construction of Moment Closure Equations (MCEs), which can be used to represent both the mean and second moments (variances and covariances) of the distribution of different parasite stages and phenomenological measures of host immunity. We apply these models to one of the best documented interactions involving free-living animal hosts--the interaction between trichostrongylid nematodes and ruminants. The analysis compares patterns of variability in experimental infections of Teladorsagia circumcincta in sheep with the equivalent wildlife situation--the epidemiology of T. circumcincta in a feral population of Soay sheep on St Kilda, Outer Hebrides. We focus on the relationship between mean parasite load and aggregation (inversely measured by the negative binomial parameter, k) for cohorts of hosts. The analysis and empirical data indicate that k tracks the increase and subsequent decline in the mean burden with host age. We discuss this result in terms of the degree of heterogeneity in the impact of host immunity or parasite-induced mortality required to shorten the tail of the parasite distribution (and therefore increase k) in older animals. The model is also used to analyse the relationship between estimated worm and egg counts (since only the latter are often available for wildlife hosts). Finally, we use these results to review directions for future work on the nature and impact of parasite aggregation.