Computer models provide a new arena of computer based scientific experimentation currently referred to as computational science. One subcomponent of this new science which we seek to advance is that of computational epidemiology. Based on existing strength in information management and computer modelling and expert systems as the vital subcomponents of computational epidemiology. Some problem-solving methods are quantitative and complex, and require computer modelling methods. Others are qualitative and fall in the domain of expert systems research. The task is to meld expert knowledge with computer modelling methods to advance epidemiologic knowledge management. Two approaches, one based on expert systems, and a second based on computer modelling will be utilized. Since the two methods appear to be different, they have generally been used separately. However, if the two are coupled, a more effective problem-solving and decision-support model may result. To test this core hypothesis, we will proceed to develop prototypes of the two systems and experiment with optimal coupling approaches using the bioepidemiologic dynamics of trypanosoma as the test bed. An outreach component will be embedded in the research environment so as to increase the number of minorities pursuing advanced studies in computational epidemiology. The research and outreach in tandem will lead to the development of resources that will form the backbone for long term research in computational epidemiology.
