The increasingly erratic and intense nature of climate factors, such as precipitation, temperature, and wind present unprecedented risks to human health. However, there is an opportunity for artificial intelligence and advanced analytics (AI/AA) to enhance our ability to adapt our reactions and systems to the impacts of climate. AI/AA can improve our understanding to describe complex, evolving, and often non-obvious relationships between climate and health factors; predict scenarios over different time horizons; and recommend interventions with trade-offs to optimize resulting health outcomes.

Despite this potential, AI/AA use cases at the intersection of climate and health remain nascent, particularly in low- and middle-income countries (LMICs), where the requisite data, analytical systems, and ecosystem conditions may not yet exist. This report discusses the current landscape of AI/AA use cases for climate-sensitive health risks and identifies two action pathways:

(1) invest in enabling data, analytical capabilities, and ecosystem conditions that are applicable across climate-sensitive health risks; and

(2) advance AI/AA use cases for a specific climate-sensitive health risk by adapting and expanding existing models, exploring modifications, or shaping foundational understanding where climate-health linkages are less understood.