ODESSA aims to address public health risks linked to air pollution, which worsens noncommunicable diseases (NCDs) such as cardiovascular disease, diabetes, cancer, and chronic respiratory illnesses, particularly in urban areas. The COVID-19 pandemic highlighted the urgent need for predictive systems to manage hospital demand and improve healthcare efficiency.
The project’s main goal is to develop an open-source WebGIS platform to forecast hospital admissions due to air pollution-related NCDs. By applying advanced data science methods and machine learning algorithms, ODESSA will support a more proactive public health response and contribute to research on air pollution and health. It also seeks to promote citizen engagement and encourage integrated health and environmental policy-making.
ODESSA will use data from emergency hospital admissions in Portugal’s National Health Service (SNS), meteorological data, information from the national air quality monitoring network, collaborative private sensors, and air quality modelling simulations. A set of code routines will be developed, tested, validated, and made publicly available to the scientific community. Although centred on the Lisbon Metropolitan Area, the project is designed to be scalable and applicable to other regions.
The initiative combines scientific and societal impact. All datasets will be shared on the Zenodo platform to promote transparency and reuse. A participatory approach will involve citizens in the platform’s development, enhancing scientific literacy and environmental awareness. ODESSA will contribute to two of the United Nations 2030 Sustainable Development Goals — SDG 3 (Good Health and Well-being) and SDG 11 (Sustainable Cities and Communities). It is also aligned with the European Green Deal and Portugal’s national Research and Innovation Agenda for Urban Science and Cities of the Future, both of which call for improved monitoring systems and stronger links between environmental and health challenges
