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