AIOLOS

Real-time detection and monitoring of respiratory epidemics by combining multi-source data integration and artificial intelligence

The AIOLOS project aims to develop a national, agile, and sustainable tool based on the real-time integration of multi-source data and the use of artificial intelligence (AI) to better detect, monitor, and manage the response to respiratory virus epidemics and pandemics.

AIOLOS will combine aggregated health data (emergency room visits, hospitalizations, virus genome sequences, GPs visits, medical test results, drug purchases, etc.) with non-health data (social media content, air quality, weather, virus detection in wastewater, mobility data, etc.) in real time. This data, already generated by various tools and actors, is still underused and fragmented.

They will be analyzed, transformed, and combined using AI methods, then displayed in an interactive dashboard for decision-makers, ensuring real-time access to information relevant to crisis management. The use of advanced AI functions will make it possible to correct biases, detect weak signals, anticipate epidemic peaks, and generate contextualized alerts.

AIOLOS will also include a mobile app for the public, designed to inform citizens about the level of risk around them (“a respiratory virus forecast”) and to support prevention strategies, in conjunction with health authorities. This app will pave the way for participatory epidemiology by encouraging citizens to report information.

A large-scale project spanning four years, AIOLOS builds on the achievements of an initial Franco-German proof of concept[1], supported as part of the France 2030 Plan. In September 2027, AIOLOS will deliver a functional regional pilot project in the Rhône population basin, and the solution will then be gradually rolled out across France in 2028 and 2029.

The AIOLOS project is led by a public-private consortium including the Hospices Civils de Lyon, Orange Business, Impact Health Care (a CRO specializing in public health and digital technology), and Biolevate (an AI start-up selected for French Tech 2030 in the 2025 promotion). The wider ecosystem of data providers and other public or private players wishing to contribute will be closely involved in the project through the AIOLOS association, which will oversee and coordinate the entire project. Sanofi will share its expertise in epidemiology and global surveillance through a skills sponsorship program with this association.

Through this integrated and open approach, AIOLOS aims to provide France with an agile, reliable, and scalable tool to strengthen the detection and management of epidemics in the face of emerging respiratory viral threats and beyond.

NB: AIOLOS will not collect or process any personal health data. Suppliers retain control over the data they make available, and consortium members do not have privileged access to the system. The data is displayed in a secure dashboard hosted in France, in accordance with national standards, ensuring data protection, trust, and regulatory compliance.

^[1] Policy makers must adopt agile signal detection tools to strengthen epidemiological surveillance and improve pandemic preparedness – ScienceDirect