Socioeconomic-informed prediction models for preventing asthma exacerbations: a PRISAAD sub-project
| Reference number | |
| Coordinator | Karolinska Institutet - Karolinska Institutet Inst f kvinnors & barns hälsa |
| Funding from Vinnova | SEK 1 000 000 |
| Project duration | November 2025 - December 2026 |
| Status | Ongoing |
| Venture | Deepened international collaborations |
| Call | Deepened collaboration with USA, UK and Singapore within Health and Life Science |
Purpose and goal
This PRISAAD project aims to integrate individual-level socioeconomic status (SES) data to enhance risk stratification and improve machine learning (ML) models for preventing asthma exacerbations.
Expected effects and result
By informing ML models with SES and integrating them into home spirometry system AsthmaTuner (MediTuner AB), the project seeks to enable early detection, reduce disease burden, and strengthen healthcare efficiency.
Planned approach and implementation
The project will (1) define key variables to construct the first Swedish HOUSES index using PRISAAD and Psych4 datasets, (2) validate this index against asthma and psychiatric outcomes while conducting a meta-analysis with the U.S. HOUSES index, and (3) develop a roadmap for technical, regulatory, and ethical integration of SES into ML models in Sweden and the U.S., with scale-up toward larger randomized controlled trials.