Environmental Effect on Health Care and Wellbeing and Active Interventions
ENACT is a European research project focused on understanding how pollution affects our health—so we can prevent diseases before they start. Using cutting-edge science, the project will develop a risk score that shows how exposure to air, noise, and light pollution may lead to chronic conditions like heart disease. This tool will help citizens, healthcare professionals, and policymakers make smarter actions to protect health, reduce financial burden, and improve quality of life in our communities.
Funders
Partners
Project information
Implementation time
01.01.2025-30.06.2028
Funder
Horizon Europe P2 Global Challenges
Research programme
Project type
Themes
Project Manager
Sari Sarlio-Siintola
Background
Through innovation and preventive strategies, we aim to lower the burden of non-communicable diseases and improve overall wellbeing.
Objectives
Develop a comprehensive model to assess the
interaction between environmental factors and non
communicable diseases (NCDs)
→Create an exposomic risk score based on multiple
environmental exposures (air, noise, light, etc.) linked
to hospitalization for acute vascular and non-vascular
NCDs.
→Translate this population-level risk model to the
individual level, enabling prediction of preclinical stages
of disease.
Build a secure, federated platform for exposomic
risk analysis
→Implement a privacy-preserving platform using
Federated and Distributed Ledger Technologies (DLT)
to enable secure data sharing and AI model training
across countries.
→Provide a suite of services—including risk scores
and visualization tools—for use by citizens, healthcare
professional
Activities
Retrospective phase
Model development
Using retrospective health data from ~400,000 patients in Belgium, ENACT will construct an exposomic risk prediction model focused on hospitalizations related to
acute NCDs.
Model validation and calibration
The predictive model will be validated and calibrated using retrospective data from five national cohorts (~600,000 patients).
Prospective phase
The population-level model is adapted into a personalised risk assessment tool. This will be achieved by integrating data from ~2,000 healthy volunteers across the five participating countries (Belgium, Bulgaria, Ireland, Italy and Spain).
Laurea’s role
Ethics work in the project including Z-inspection® process
Data management plan
Publications
Ethics of AI – viewpoints from MANOLO and ENACT projects
Eettisesti kestävän innovaation edellytykset: Etiikka, lainsäädäntö ja aineistonhallinta tekoälyä hyödyntävässä ENACT-hankkeessa
Sustainable development goals
Contacts
-
Laura Tahvanainen
Senior Lecturer
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