Science and Technology
The PULSE project will pioneer the development and testing of dynamic spatio-temporal health impact assessments using geolocated population-based data.
PULSE project combines a multidisciplinary approach involving different technologies and tools for different types of users or stakeholders and will work on the identification of the user need and definition of detailed specifications for the tools and technologies that will be developed in the project. It will also develop a comprehensive scale to measure the degree of acceptance and use of an HiAP approach in urban environments.
This activity includes:
- Definition and implementation of the the strategy and the apps for collecting individual citizen data (personal health behaviors and well-being);
- Definition and implementation of the strategy and technical specifications for developing PULSE WebGIS;
- Definition and implementation of the strategy and framework for the PULSE urban game: Engineering Health and Well-being;
- Definition and implementation of the strategy for persuasive, adaptive behavior change in the PULSE Personalized Risk Assessment App;
- Provide mechanisms for the formal representation of the acquired personal data (health data, behavioral data, well-being data);
- Development and deployment of a comprehensive Big Data cloud analytics tool.
PULSE will deliver a novel set of multiscale Risk and Resilience models (PULSE models), redefining the public health approach to two major diseases (Asthma and T2D), and introducing a public health focus on well-being.
The PULSE consortium aims to improve the existing approach by exploiting synergies between
NASA (i.e., Landsat-8) and ESA (i.e., Sentinel-2) satellites to overcome the rather coarse temporal resolution (25 days) of a single sensor by considering and merging measurements by multiple sensors. The spatial resolution of both sensors is comparable (20-30 m), and provides enough details to characterize neighbourhood and population areas, down to census
parcels, and possibly at a finer scale than currently available population models. This layer of information will constitute an invaluable input to urban air quality models, especially with regard to the relationship between air quality and human health.
Mechanistic and probabilistic predictive modelling of environmental and clinical risk factors in T2D and Asthma
Models will be developed and tested on data from medical records / ambulatory patient visits (rather than from clinical trials) ensuring that the models are more accurate for real-time use. Enhanced models for prediction and detection will support prevention efforts and allow for the improvement of the diagnosis and treatment of T2D.
Another key innovation will be the recalibration of the models against each specific population, a step recently demonstrated to be of crucial importance for rendering model accuracy acceptable.
Furthermore, the availability of data coming from several different cities located in different countries, will allow to us to assess the model performance on different populations, and to understand the importance of model recalibration/tuning on the specific population. This this will allow for greater precision regarding prediction and greater accuracy regarding interventions.
PULSE will focus on defining a comprehensive, multidisciplinary model of urban well-being. The model will incorporate the defining characteristics of smart cities (as defined in ISO standards), and healthy cities (WHO criteria), state-of-the-art research in psychology and sociology, and findings of major policy reports on well-being and governance. The model will draw on data from several sources: government data (including open data); social media data, data from the PULSE Health app and the PULSE Well-being app.
The technical architecture for the PULSE Public Health Observatories will be defined, along with the technical specifications for the PULSE WebGIS. This will include the integration of existing and new data sets, visualizations and models into each Observatory. Each Observatory will be linked in an ecosystem enabling stakeholders, including citizens, municipalities, entrepreneurs and businesses to access, query and extract meaning and insights from the knowledge base in the Observatories. The PULSE Communities of Practice (CoPs) will be created, and linked across test bed sites. The PULSE Innovation Council, and Education and Training Team, will define work flows and processes to deliver outcomes. The Council and the Team will leverage the PULSE knowledge infrastructure (Observatories, WebGIS, Communities of Practice) to operationalize the innovation and education/training strategies.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No GA727816.
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