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Diabetes in pregnancy (DIP) is an increasing public health priority in theAustralian Capital Territory, particularly due to its impact on risk fordeveloping Type 2 diabetes. While earlier diagnostic screening results ingreater capacity for early detection and treatment, such benefits must bebalanced with the greater demands this imposes on public health services. Toaddress such planning challenges, a multi-scale hybrid simulation model of DIPwas built to explore the interaction of risk factors and capture the dynamicsunderlying the development of DIP. The impact of interventions on healthoutcomes at the physiological, health service and population level is measured.Of particular central significance in the model is a compartmental modelrepresenting the underlying physiological regulation of glycemic status basedon beta-cell dynamics and insulin resistance. The model also simulated thedynamics of continuous BMI evolution, glycemic status change during pregnancyand diabetes classification driven by the individual-level physiological model.We further modeled public health service pathways providing diagnosis and carefor DIP to explore the optimization of resource use during service delivery.The model was extensively calibrated against empirical data.

Multi-Scale Simulation Modeling for Prevention and Public Health Management of Diabetes in Pregnancy and Sequelae