The epidemiology of trypanosome infections of Glossina pallidipes was studied at a riverine site in the Zambezi Valley, Zimbabwe for a period of 13 months. Over 9000 flies were captured using a single trap. These flies were dissected, screened for trypanosome infection, sexed, and aged using both wing fray and (for females) ovarian category indices. Midgut infections were identified to species using recently developed DNA probes. The overall prevalence of mature infections was 5.5%, comprising 3.1% Trypanosoma vivax-type and 2.4% T. congolense-type (which included very low prevalences of T. brucei, T. simiae and another Nannomonas species). The prevalence of infection increased with age. For T. vivax-type infections in flies aged by ovarian category this relationship could be described by a simple 'catalytic' model assuming a constant per capita rate of infection. For T. congolense-type infections this model tended to over-estimate prevalence in older age classes, implying that the rate of infection decreases with age, and/or that infected flies have higher mortality rates, and/or that a significant fraction of the population is resistant to infection. Prevalences of infection also varied between months. This variation was more marked for T. vivax-type infections and was negatively correlated with both temperature and rainfall. The shape of the age-prevalence relationship, however, did not vary significantly between months. These observations are not fully explained by variation in the age-structure of the tsetse population and are consistent with temporal variation in the rate of infection (rather than in the trypanosome developmental period or in effects of infection on fly mortality). Possible causes of this variation are discussed.

Recent research has shown that many parasite populations are made up of a number of epidemiologically distinct strains or genotypes. The implications of strain structure or genetic diversity for parasite population dynamics are still uncertain, partly because there is no coherent framework for the interpretation of ¢eld data. Here, we present an analysis of four published data sets for vector-borne microparasite infections where strains or genotypes have been distinguished: serotypes of African horse sickness (AHS) in zebra; types of Nannomonas trypanosomes in tsetse £ies; parasite-induced erythrocyte surface antigen (PIESA) based isolates of Plasmodium falciparum malaria in humans, and the merozoite surface protein 2 gene (MSP-2) alleles of P. falciparum in humans and in anopheline mosquitoes. For each data set we consider the distribution of strains or types among hosts and any pairwise associations between strains or types. Where host age data are available we also compare age^prevalence relationships and estimates of the force of infection. Multiple infections of hosts are common and for most data sets infections have an aggregated distribution among hosts with a tendency towards positive associations between certain strains or types. These patterns could result from interactions (facilitation) between strains or types, or they could re£ect patterns of contact between hosts and vectors. We use a mathematical model to illustrate the impact of host^vector contact patterns, ¢nding that even if contact is random there may still be signi¢cant aggregation in parasite distributions. This e¡ect is enhanced if there is non-random contact or other heterogeneities between hosts, vectors or parasites. In practice, di¡erent strains or types also have di¡erent forces of infection. We anticipate that aggregated distributions and positive associations between microparasite strains or types will be extremely common.

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The prevalence of various species and subgroups of trypanosomes in the Sinfra area of Côte d'Ivoire was determined using the polymerase chain reaction (PCR). Using this technique to amplify specific satellite DNA targets, it was possible to identify developmental-stage trypanosomes in the midguts and the proboscides of tsetse without expansion of parasite populations. The predominant tsetse species in the area was Glossina palpalis, while G. pallicera and G. nigrofusca were also present. Microscopical examination of 811 non-teneral flies revealed an infection rate of 14% in midguts and/or proboscides. Three subgroups of Trypanosoma congolense (Savannah, Forest & Kilifi), T. simiae, T. godfreyi, West African T. vivax and T. brucei ssp. were identified using PCR. T. congolense Forest was the most abundant of the Nannomonas trypanosomes. Approximately 40% of all infections were mixed, and there was a significantly higher prevalence of apparently mature T. brucei ssp. trypanosomes than has previously been reported. The present study demonstrates that PCR facilitates the easy identification of mature trypanosome infections in tsetse, providing a reliable estimation of trypanosomiasis challenge.

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