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首页> 外文会议>International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation >Multi-scale Simulation Modeling for Prevention and Public Health Management of Diabetes in Pregnancy and Sequelae
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Multi-scale Simulation Modeling for Prevention and Public Health Management of Diabetes in Pregnancy and Sequelae

机译：糖尿病和后遗症糖尿病预防和公共卫生管理的多尺度仿真模型

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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.
机译：怀孕糖尿病（DIP）在澳大利亚首都特区日益成为公共卫生的重中之重，特别是由于其对发展为2型糖尿病的风险的影响。尽早进行诊断性筛查可提高早期发现和治疗的能力，但必须在这种益处与对公共卫生服务提出的更高要求之间取得平衡。为了应对此类规划挑战，建立了DIP的多尺度混合仿真模型，以探索风险因素的相互作用并捕获DIP发展背后的动态。在生理，卫生服务和人口层面，对干预措施对健康结果的影响进行了测量。在模型中，特别重要的是一个基于β细胞动力学和胰岛素抵抗的，代表血糖状态潜在生理调节的间隔模型。该模型还模拟了个体水平生理模型驱动的持续BMI演变，怀孕期间血糖状态变化和糖尿病分类的动力学。我们进一步为提供DIP诊断和护理的公共卫生服务路径建模，以探索服务提供过程中资源利用的优化。该模型已针对经验数据进行了广泛校准。

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