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Mathematical models assist AIDS researchers.


 Mathematicians and computer scientists have developed mathematical models and computer programs designed to help understand Acquired Immune Deficiency Syndrome (AIDS). Currently, there are more than 100 models of the AIDS epidemic. Regardless of the level of complexity, the model can help clinicians or policymakers who must decide the most effective course of action when confronted with an AIDS dilemma. In general, there are 4 types of AIDS models: simple analytic; extrapolation; convolution; and computer simulation. The simple analytic type tries to elucidate the dynamics of the epidemic itself. Extrapolation models utilize historical AIDS data to forecast future disease trends. Convolution models use more complex epidemiological data to assess the impact of the epidemic. John Bongaarts, of the Population Council, has developed a sophisticated computer simulation model designed to be used by a developing country. The model requires more input variables than the World Health Organization (WHO) model and also incorporates data about people's sexual behavior. By comparison, Sokal has developed a relatively simple computer simulation model that analyzes reproductive mortality among adult women. 1 of its possible applications is utilization by family planning managers who are struggling with the dilemma about AIDS and contraception. Sokal's model uses 5 fixed parameters, which the user does not alter: the projection period is from 1988-2000; without contraception there is a 30% pregnancy rate each year; oral contraceptives reduce the pregnancy rate by 80% and do not influence the risk of human immunodeficiency virus (HIV) transmission; condoms reduce the pregnancy rate by 67% and prevent 50% of HIV transmission; and 4 contraceptive use patterns are compared -- none, OCs, condoms, and both methods. At this point in their evolution, all models are only as good as the data entered into them. Well designed and applied, models can be of value to health professionals and other decision makers working to understand AIDS and reduce its incidence.
