AI, Climate, and Health: How Machine Learning Is Reshaping Environmental Risk, Disease Prediction, and Public Health

The Environment, Technology, and Health Intersection Series explores the complex relationships among environmental change, technological innovation, human health, and society. The series examines how emerging technologies, environmental conditions, and social systems interact to shape health risks, opportunities, policies, and public-health responses.

Drawing on perspectives from public health, environmental health, climate science, technology, data and artificial intelligence, and environmental governance, the series connects evidence and practical application. Its books address issues such as climate-sensitive health risks, environmental exposure, disease prediction, digital transformation, occupational health, sustainability, health equity, and the governance of emerging technologies.

A central principle of the series is that understanding risk is only part of the challenge. Evidence, prediction, technology, and policy must ultimately connect to decisions and actions that protect health and support resilient communities. The series therefore distinguishes between what is established, what is emerging, what remains experimental, and what represents a conceptual or policy proposal.

Designed for public-health professionals, environmental and health practitioners, researchers, students, policymakers, and informed readers, the series aims to make interdisciplinary knowledge accessible without losing scientific and analytical rigor.

Environment, Technology, and Health Intersection Series provides a framework for understanding—and responsibly responding to—the changing relationships between the environments we inhabit, the technologies we develop, and the health outcomes we experience.