Prediction and support system for the comprehensive management of the evolution and use of resources in pandemics situations.
The PROCEED project aims to create an augmented epidemiological model to support decision-making through the collection, integration, and analysis of heterogeneous data sources (health, mobility, environment, wastewater and social).
Within the framework of the project, a new system for predicting and supporting the comprehensive management of pandemics is developed and deployed, defined as a personalised infrastructure and offering tools that allow managers, clinical professionals and patients to access data, results, indicators, predictions and recommendation throughout the various stages of the epidemic cycle.
The new system developed by PROCEED will make it possible to anticipate the detection of the pandemic and optimise the response through predictive management, reducing the risks of to the most vulnerable groups and optimising the use of resources by allocating them to those services, sectors and populations that require greater attention.
On the other hand, the convergence of data analysis, optimisation, simulation, and artificial intelligence technologies, together with the knowledge of health experts, will allow the co-generation of models for monitoring and studying the pandemic. These models will be used to assess the clinical course of the disease, evaluate infection sources, study and predict the geographical evolution of the epidemic, establish infection rates by geographical areas, as well as environmental factors that affect the biology of the virus and its epidemic cycle.
The PROCEED project is formed by Eurecat through its Digital Health Unit, the Applied Artificial Intelligence Unit, the Water, Air and Soil (WAS) Unit, the Omic Sciences Unit and the Big Data & Data Science Unit.