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This study presents a counterfactual inference approach for ordinary differential equations (ODEs) models. The methodology is applied to a model describing blood glucose regulation to assess the effects of personalized physical activity plans on type 2 diabetes progression. The analysis demonstrates how responses to physical activity vary among individuals based on \(\beta \) -cells mass and insulin sensitivity, resulting in diverse sets of counterfactual physical activity plans. This approach can eventually help identify individuals who might benefit from early diabetes prevention measures via personalized physical activity plans.

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Counterfactual Inference Using Ordinary Differential Equations to Assess the Effect of Physical Activity on Type 2 Diabetes Onset

  • 会议论文

  • 发表日期：

    2025年

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  • Marta Lenatti,
  • Marco Zaffalon,
  • Alessandro Antonucci,
  • Pierluigi Francesco De Paola,
  • Lea Multerer,
  • Maurizio Mongelli,
  • Alessia Paglialonga,
  • Laura Azzimonti

摘要

This study presents a counterfactual inference approach for ordinary differential equations (ODEs) models. The methodology is applied to a model describing blood glucose regulation to assess the effects of personalized physical activity plans on type 2 diabetes progression. The analysis demonstrates how responses to physical activity vary among individuals based on \(\beta \) -cells mass and insulin sensitivity, resulting in diverse sets of counterfactual physical activity plans. This approach can eventually help identify individuals who might benefit from early diabetes prevention measures via personalized physical activity plans.