The MePreCiSa project (Precision Medicine for Healthy Cities) concluded this December, and during its duration, the technical team has worked on developing a new cloud-based prediction platform using Big Data.

This project has developed a cloud platform for large-scale data analysis in cities. Combining mobility, health, and environmental indicators to enable integrated studies that generate more accurate predictions for decision-making, MePreCiSa has developed an open platform for data analytics, visualization, and prediction in the cloud.

Platform Usage Results

To demonstrate the platform’s potential applications, MePreCiSa has provided various use cases with real-world situations and data.

The first use case is air quality, in which potential risks have been identified with greater precision. In this case, in the Catalonia region, data on mobility, exposure to pollutants, and disease prevalence have been integrated to construct a more accurate risk map.

Thus, by measuring mobility using mobile phone data, identifying the presence of fine particulate matter in the air as a pollutant, and determining the prevalence of cardiovascular diseases, such as hypertension, the project has helped to identify vulnerable groups and design specific policies tailored to their needs.

The second use case involves epidemic control. In this case, mobility data has been integrated to facilitate epidemic control. The analysis of national mobility and infections during the COVID-19 pandemic has allowed for the creation of a model capable of anticipating transmission patterns and the impact of different preventive measures.

In this way, the project has been able to identify the most effective strategies before implementing them, facilitating decision-making.

It can be said, therefore, that although there is still a long way to go, the MePreCiSa project has provided a new approach to the health management model, impacting prevention and crisis management.