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Optimization of budgeting type 2 diabetes through modeling disease burden

Diabetes is one of the deadliest non-communicable diseases that imposes huge costs on societies. The imposed cost, which is a direct consequence of the incidence of this disease, is known as the burden of disease that is commonly quantified by a summarized health indicator known as DALY (Disability Adjusted Life Years). Due to the limitation of financial resources, in order to minimize the burden of the disease an optimized policy is required for budget distribution among the different fields associated with this disease, i.e. monitoring and treatment. In this research, by exploring the existing models, a Markov chain model is developed for modeling the burden of type 2 diabetes. Simulation of 10-year DALY on this model shows that the usual 50/50 budget distribution policy between monitoring and treatment, which is generally used in developing countries, is not an appropriate strategy for the current status of this disease. In fact, a better policy is to focus more on monitoring in initial years in order to discover undiagnosed diabetic people.