About the Project
The environment is one of the most crucial determinants of health. The Global Burden of Disease report estimates an emerging impact in terms of disability and reducing the quality of life worldwide, particularly for the aging populations.
One of the root causes of this decline is likely to derive from the interaction of socio-environmental risk factors and sub-clinical conditions and the consequent increase of the primary non-communicable disease (dementia, COPD, cerebrovascular and chronic ischemic heart diseases).
This proposal aims to develop a technological toolkit for dynamic, intelligent HIA toolkit to predict the health impact of health-related features, forecasting the trajectories of disability and quality of life reduction. This method will use environmental, socioeconomic, geographical, and clinical characteristics, managed and elaborated with a federated learning architecture.
The generated models will be adjusted for lifestyle and individual conditions data sourced from large population-based digital surveys.
The models will be trained and validated on three different exposures to the steel plants’ pollution: Taranto in southern Italy, Rybnik in Poland, and Flanders in Belgium.
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