MATHEMATICAL MODEL FOR DETERMINING DIABETES IN CAPE COAST - Jacobs, Bernard Allotey (AFRICAN JOURNAL OF APPLIED RESEARCH, 2016)
Diabetes is said to be one of the rising killer diseases globally, claiming one life every eight seconds and a limb lost at every 30 seconds. This has become a burden in the country as the situation has the tendency to weaken the workforce of the nation if much awareness is not induced. The aim of this project is to find out how our body’s metabolism is linked to the disease by modeling the interaction between insulin and glucose. The objective is to use the model to analyse a clinical test for the determining of various forms of diabetes. A nonlinear least square method is used to determine the coefficient parameters of the system based on actual data from Glucose Tolerance test (GTT). The simulations also provide an indicator to diagnose a diabetic condition. Central Regional Teaching Hospital was used as the population and three patients were selected at random for the studies of which one was hyperglycemic (subject B), diabetic (subject C) and the other non-diabetic (subject A). The error between the simulated data and the experimental data was calculated to be very small in subject A and subject C. The case with subject B indicate that our model described above can only be used to diagnose mild diabetes or pre-diabetes, since it was assumed throughout that the deviation of g of G from its optimal value Go is small.