A new health management model

Discover our project: an open platform for data analytics, visualisation and prediction in the cloud

The most advanced technology for decision making

Precision Medicine for Healthy Cities

From the MePreCiSa project we have developed a pioneering prediction model that integrates mobility, health and environmental data for the first time in a single platform. We provide an open cloud platform for health management in complex scenarios, addressing the challenge presented by urban centres in terms of exposure to pollutants and their impact on health, as well as control of the spread of diseases.

MePreCiSa impact

Prevention
Providing analysis and predictions of the impact of environmental factors.

Crisis management
Providing models of epidemic spread.

Multiple layers of analysis

Integrated into a single platform

Mobility and dynamic population

By analysing anonymized mobile-based mobility data, we study dynamic patterns of population mobility, presence, and exposure.

Environmental indicators

We use high-resolution data on the concentration of air pollutants to measure dynamic exposure and detect areas where low air quality affects population health.

Disease incidence

Our platform includes clinical registry data with which we map the spatio-temporal incidence of different diseases related to environmental and infectious factors.

By integrating and fusing multiple layers of information we can understand the relationship between the different factors that affect health on a large scale. This allows us to create more accurate models and forecasts. In addition to relating the incidence of diseases to environmental factors, it allows epidemiological studies to be carried out considering population mobility and activity patterns.

Our platform in action

Discover the results of our use cases

Mobility, Air quality and Health

We combine population mobility data with air quality data to estimate the dynamic exposure of people. Dynamic exposure is used to guide epidemiological studies that improve understanding of the risk that exposure to poor air quality poses in the development of respiratory and cardiovascular diseases, among others. This allows us to identify exposure sources that guide the design of preventive measures.

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Epidemic spread

We implemented an epidemic simulator that integrates mobility data to simulate scenarios and design containment measures and effective vaccination strategies. These types of tools are key to supporting decision-making and controlling potential outbreaks of new emerging diseases.

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Mobility and Wastewater Epidemiology

Wastewater epidemiology is a key tool for the early detection of disease outbreaks and emergence of antibiotic-resistant bacteria among other things. We integrate dynamic patterns of population mobility and activity to improve the interpretation of biomarkers quantified in different wastewater treatment plants.

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