Project Full Title
Strategic Health Initiatives for Effective Disease Prevention
EU Workprogramme
Horizon Europe – Work Programme 2023-2024 – Cluster Health
HORIZON-HLTH-2024-STAYHLTH-01-05-two-stage: Personalised prevention of non-communicable diseases – addressing areas of unmet needs using multiple data sources
Grant Agreement No.
101156751
Duration
48 months
Starting Date: December 1, 2024
Expected Ending: November 30, 2028
Project Main Website
Visit the SHIELD website here!
Consortium
- Hi Iberia Ingenieria Y Proyectos (SPAIN) (Coordinator)
- Servicio Madrileno De Salud (SPAIN)
- Universidad Politecnica De Madrid (SPAIN)
- Consorzio Per La Ricerca Nell’Automatica E Nelle Telecomunicazioni C.R.A.T. (ITALY)
- Universita Degli Studi Di Bari Aldo Moro (ITALY)
- Quavlive Srl (ITALY)
- University Of Limerick (IRELAND)
- University of Geneva & University of Geneva Hospitals (SWITZERLAND)
CRAT Key People
- Prof. Francesco Delli Priscoli
- Prof. Antonio Pietrabissa
- Prof. Alessandro Giuseppi
- Dr. Ing. Andrea Wrona – WP7 and T7.1 Leader
- Ing. Federico Baldisseri – T6.3 Leader
- Dr. Ing. Danilo Menegatti – T6.4 Leader
- Mr. Mohab Atanasious
- Ms. Valentina Becchetti
Project Description
The rising prevalence of Non-Communicable Diseases is pushing countries to explore initiatives to lessen their burden. In this context, SHIELD introduces an innovative method to prevent cardiovascular diseases (CVD) and type 2 diabetes (T2DM) at every stage, recognizing their interrelation. By leveraging advanced AI, SHIELD delivers personalized interventions based on a hierarchical model that categorizes patients into low, moderate, and high-risk groups using continuous risk stratification and disease progression tools.
Initial assessments consider genetics, demographics, socio-economic status, environment, behavior, and existing conditions, using datasets like SHARE, ELSA, and hospital records (4,500+ patients). As the disease progresses, factors such as polypharmacy, treatment adherence, wearables data, psychosocial aspects, PROMs, and PREMs are incorporated, enabling tailored interventions and real-time alerts via the SHIELD dashboard.
SHIELD also emphasizes data quality and security, employing a standardized data homogenization model and federated learning to keep sensitive data local, with transparency ensured by explainable ML tools. Interventions are delivered through mobile apps that offer resources, recommendations, education, and local services, enhanced by optimization algorithms and a professionally overseen chatbot.
The project will be validated in three pilots (Spanish, Italian, Swiss) involving over 2,300 individuals over two years, aiming to assess the cost-effectiveness and efficacy of its prevention strategy and provide insights for broader primary prevention pathways.