Mathematical models of infectious diseases have a long history with early models offering important insight into epidemics and guidance for designing effective vaccination strategies. Increasing availability of genetic data offers new opportunities to understand the fundamental mechanisms of how an infection plays out within a single host. In this talk I will present a model for African sleeping sickness, a potentially fatal disease caused by the parasite trypanosome. Typansomes are among the many parasites that exhibit genetic variation as a mechanism to sustain chronic infections within their hosts. Other examples where genetic variation is important are influenza and malaria infection. In the case of the trypansome parasite it obtains protection from the host's immune response by switching between genetically distinct parasite variants. Typical trypanosome infections consist of oscillations in the level of infection present in the hosts, where each peak is composed of a group of genetically distinct parasite variants. In this talk I will present a mathematical model used to investigate within-host dynamics of African trypanosomes and examine the role and limitations of trypansome genetic variation.