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 field 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 flies; 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 reflect patterns of contact between hosts and vectors. We use a mathematical model to illustrate the impact of host–vector contact patterns, finding that even if contact is random there may still be significant aggregation in parasite distributions. This effect is enhanced if there is non–random contact or other heterogeneities between hosts, vectors or parasites. In practice, different strains or types also have different forces of infection. We anticipate that aggregated distributions and positive associations between microparasite strains or types will be extremely common.