Patterns of infection: using age prevalence data to understand the epidemic of HIV in South Africa.

South Africa is experiencing an explosive epidemic of HIV/AIDS, with about one in four women attending ante-natal clinics nationwide being HIV-positive. In order to understand the natural history of the epidemic, to design and target interventions to manage it and to evaluate the impact of interventions that are implemented, it is essential to gather information on the patterns of infection. In particular it is important to know how these vary with gender, age, migrancy status and between urban and rural settings. Ideally, one should measure age-specific incidence but this is difficult to do. Many datasets are available, however, on age-specific prevalence of infection and these are used to investigate the risk of infection with age among a number of different populations. The populations under consideration include women attending ante-natal clinics, urban and rural populations, migrant workers and commercial sex workers. Data are also presented from one work-based survey and from a study of cancer patients at a major hospital in Soweto. We were able to identify four different patterns of infection among a) women attending ante-natal clinics; b) women in the general population; c) men in the general population; and d) migrant workers. It is interesting that we were unable to show differences between urban and rural populations. Furthermore, the patterns of infection appear to be fairly constant over time, although as the epidemic saturates and reaches a steady state this must change. These data highlight, in particular, the extremely high risk of infection among 15-25-year-old women and among migrant workers of all ages. They should serve not only to highlight the urgency of the situation and the need to deal with the spread of infection effectively, but should also provide a basis for detailed epidemiological modelling, which can be used to predict the future course of the epidemic, plan an effective response and evaluate the impact of interventions. [ABSTRACT FROM AUTHOR]