Lay summary
Type 2 Diabetes Mellitus (T2DM) affects five percent of Aotearoa's population, with a higher prevalence among Māori and Pacific Islanders, indicating a pressing need for precision prevention strategies. Despite robust public health efforts, T2DM incidence continues to rise in Aotearoa. Human Digital Twins (HDT), which employ computer simulations to predict individual responses to real-world conditions, offer promising solutions for precision health. This research aims to develop and validate a digital human twin model for T2DM, specifically for individuals recently diagnosed or at high risk of the disease. Our approach involves constructing an HDT-T2DM by creating a digital twin model and then utilizing real-world sensor data to validate its effectiveness in reversing or preventing T2DM. By employing cutting-edge technology and data-driven insights, we aspire to provide personalized solutions that can combat the rising tide of T2DM in Aotearoa, particularly among at-risk populations such as Māori and Pacific Islanders.