Environmental Stressors and Light Pollution in Ocular and Dermatological Disease
This ENACT use case examines how environmental factors, in particular UV radiation exposure, air pollutants, temperature, and greenness of the environment, affect ocular and dermatological health in the adult and aging population of South-East Ireland. The study is structured in two complementary phases: a retrospective analysis of long-term exposures linked to clinical records, and a prospective monitoring study capturing real-time personal exposure.
The retrospective phase links multi-year environmental exposure reconstructions from national monitoring networks and gridded models with dermatology, plastic-surgery, and ophthalmology records for adults with and without UV-related skin and eye disease. Environmental predictors include direct and ground-reflected UV radiation, temperature, humidity, air pollutants (PM₂.₅, PM₁₀, NO₂, O₃), noise, indoor air quality, seasonality, and geolocation, complemented by socio-economic and basic individual characteristics where available. Analyses focus on quantifying associations between cumulative environmental exposures and the incidence, onset, and severity of UV-related skin and ocular conditions, using statistical and AI-based exposomic models within secure national data environments.
The prospective phase consists of a 12–18-month monitoring study of approximately 80–100 adult volunteers living or working in the region. Environmental wearables and mobile sensors measure real-time personal exposure to UV radiation, co-pollutants, meteorological variables, noise, indoor air quality, and location, while questionnaires capture behaviours relevant to UV exposure and protection. Short-term changes in skin and eye health are analysed and used to calibrate and validate the models developed in the retrospective phase.
Both phases will be integrated using advanced analytical methods, including Bayesian modelling and Space-Time Graph Neural Networks (ST-GNNs), to detect, model, and predict population-level disease patterns associated with long-term environmental exposure.
The use case further aims to support municipal and public-health decision-making by evaluating the potential impact of environmental or policy interventions introduced during the project period (e.g., adjustments to street-lighting to reduce light pollution, improvements in shade infrastructure, or air-quality measures). These interventions are analysed at the population or area level.
Ultimately, the findings will inform proactive mitigation strategies for both health services and local authorities, enabling data-driven planning, improved environmental-risk forecasting, and enhanced care pathways for communities most affected by environmental stressors.