We analysed data on the abundance and distribution of 26 species of mesostigmate mites with different feeding habits collected from bodies of small mammalian hosts in 2 geographical regions (West Siberia and Argentina). We tested whether prevalence of a mite can be reliably predicted from a simple epidemiological model that takes into account mean abundance and its variance. We theorized that the difference between prevalence predicted from the model and observed prevalence would be smallest in obligatory haematophagous mites, intermediate in facultatively haematophagous mites and greatest in non-haematophagous mites. We also theorized that prevalence of mites from the region with sharp seasonality (Siberia) would be predicted accurately only if host number would be taken into account. We found that the success of a simple epidemiological model to predict prevalence in mites was similar to that reported earlier for other ectoparasitic arthropods. Surprisingly, the model predicted prevalence of obligatory exclusively haematophagous mites less successfully than that of mites with other feeding habits. No difference in the model performance between mites occurring in the 2 geographical regions were found independent of whether the model took the number of hosts into account.

Epidemiological modelling can be a useful tool for the evaluation of parasite control strategies. An age-structured epidemiological model of intestinal helminth dynamics is developed. This model includes the explicit representation of changing worm distributions between hosts as a result of treatment, and estimates the morbidity due to heavy infections. The model is used to evaluate the effectiveness of different programmes of age-targeted community chemotherapy in reducing the amount of morbidity due to helminth infection. The magnitude of age-related heterogeneities is found to be very important in determining the results of age-targeted treatment programmes. The model was verified using field data from control programmes for Ascaris lumbricoides and Trichuris trichiura, and was found to provide accurate predictions of prevalence and mean intensities of infection during and following different control regimes.

Infectious diseases may have multiple infectious stages with very different epidemiological attributes,including infectivity and disease progression. These stages are oftenassumed to have exponentially distributed durations in epidemiological models. However,models that use the exponential distribution assumption (EDA) may generate biased andeven misleading results in some cases. This discrepancy is particularly damaging if the modelsare employed to assist policy-makers in disease control and interventions. This paperstudies a mathematical model that includes multiple infectious stages and general distributionsfor the stage durations (with the exponential distribution as a special case). Formulasfor the control reproductive number, Rc, and the basic reproductive number, R0, are derived,which can be conveniently applied to models in which specific stage distributions areassumed. It is also shown that the disease dynamics are determined by the reproductivenumbers.

Although age-related heterogeneity of infection has been addressed in variousepidemic models assuming a demographically stationary population, only a few studies haveexplicitly dealt with age-specific patterns of transmission in growing or decreasing population.To discuss the threshold principle realistically, the present study investigates an age-duration-structured SIR epidemic model assuming a stable host population, as the first scheme toaccount for the non-stationality of the host population. The basic reproduction number R0is derived using the next generation operator, permitting discussions over the well-knowninvasion principles. The condition of endemic steady state is also characterized by usingthe effective next generation operator. Subsequently, estimators of R0 are offered which canexplicitly account for non-zero population growth rate. Critical coverages of vaccination arealso shown, highlighting the threshold condition for a population with varying size. Whenquantifying R0 using the force of infection estimated from serological data, it should beremembered that the estimate increases as the population growth rate decreases. On thecontrary, given the same R0, critical coverage of vaccination in a growing population would behigher than that of decreasing population. Our exercise implies that high mass vaccinationcoverage at an early age would be needed to control childhood vaccine-preventable diseasesin developing countries.

We tested whether the prevalence of ticks can be predicted reliably from a simple epidemiological model that takes into account only mean abundance and its variance. We used data on the abundance and distribution of larvae and nymphs of 2 ixodid ticks parasitic on small mammals (Apodemus agrarius, Apodemus flavicollis, Apodemus uralensis, Clethrionomys glareolus and Microtus arvalis) in central Europe. Ixodes trianguliceps is active all year round, occurs in the study area in the mountain and sub-mountain habitats only and inhabits mainly host burrows and nests, whereas Ixodes ricinus occurs mainly during the warmer seasons, occupies a large variety of habitats and quests for hosts outside their shelters. In I. ricinus, the models with k values calculated from Taylor's power law overestimated prevalences. However, if moment estimates of k corrected for host number were used instead, expected prevalences of both larvae and nymphs I. ricinus in either host did not differ significantly from observed prevalences. In contrast, prevalences of larvae and nymphs of I. trianguliceps predicted by models using parameters of Taylor's power law did not differ significantly from observed prevalences, whereas the models with moment estimates of k corrected for host number in some cases under-estimated relatively lower larval prevalences and over-estimated relatively higher larval prevalences, but predicted nymphal prevalences well.