Health and Climate change: forecasting and prevention.

The project addresses the growing health impacts of climate change by integrating high-resolution environmental data with population-based health indicators to build probabilistic forecasting tools for prevention and planning. It targets outcomes such as respiratory and cardiovascular morbidity and mortality, infectious disease dynamics, and heat-related events in urban and rural settings.​

Methodologically, the project combines Bayesian hierarchical models, spatio-temporal statistics and time-series forecasting (e.g. INLA, BSTS and related approximate Bayesian inference) to capture complex dependencies between climate drivers, air pollution, and health outcomes while fully propagating uncertainty. The toolbox will include interpretable early warning indicators, scenario projections under different climate and mitigation pathways, and decision-support metrics relevant for public health authorities and local policymakers.​

The consortium is particularly interested in partners who can:

• Provide high-quality health or environmental datasets, or access to cohorts, registries, or surveillance systems at local, national or European level.​

• Contribute expertise in epidemiology, exposure assessment, climate services, or health impact assessment, including stakeholders from public health agencies, municipalities, and NGOs.​

• Co-develop and pilot test forecasting and prevention tools (dashboards, risk maps, decision-support systems) in real-world contexts such as heat-health action plans, urban adaptation strategies, or hospital preparedness.​

The long-term vision is to establish a sustainable, interdisciplinary collaboration that can respond to future Horizon Europe calls on climate, environment and health, and to build a European reference network on climate-related health risk forecasting and prevention