Integrating Climate, Health, and AI: A Blueprint for Resilient Public Health Systems

Climate change is emerging not only as an environmental crisis but also as one of the gravest public health challenges of our time. A group of researchers from the Harvard T.H. Chan School of Public Health, the University of Washington, Stanford University, the University of California, Irvine, the World Health Organization, the Madagascar Ministry of Public Health, and several Malagasy government agencies and institutes have proposed a bold new framework called Climate-Smart Public Health (CSPH). Published in The Lancet Planetary Health in 2025, their work outlines an ambitious approach to integrate health, climate, and environmental monitoring into a unified system. This framework is designed to anticipate, manage, and mitigate the health consequences of a warming world by using artificial intelligence, big data, and community knowledge to protect the most vulnerable.

Madagascar: The Epicenter of Climate-Health Risks

Madagascar serves as the pilot country for operationalizing CSPH, and the choice is deliberate. The island is one of the most climate-vulnerable places on Earth, facing frequent cyclones, prolonged droughts, and deadly heatwaves. More than 80 percent of its population lives in poverty, while malnutrition stunts the growth of nearly half of all children. Child mortality rates remain high, and maternal deaths are among the worst globally. These health crises are compounded by environmental pressures such as deforestation and ocean warming, which disrupt food supplies and fuel the spread of diarrhoeal and vector-borne diseases like malaria. For researchers, Madagascar offers both urgent challenges and an opportunity to test how integrated systems can save lives in fragile contexts.

Building the Climate-Health Data Engine

At the heart of CSPH lies a powerful data platform that integrates clinical records from more than 2,700 Malagasy health clinics with environmental and climate indicators. Traditionally, health and environmental data existed in isolation, limiting understanding of how the two interact. Now, records of over 60 health conditions, ranging from infectious to nutritional, are being cross-analyzed with satellite-derived rainfall, soil moisture, cyclone tracks, and even air quality measurements. By geocoding and timestamping this information, researchers can reveal how weather shocks translate into disease outbreaks and malnutrition. For example, falling soil moisture levels can be directly linked to reduced crop yields and then mapped against rising rates of child wasting or stunting. Similarly, harmful algal blooms in warming seas, which contaminate fish and cause poisoning, can be detected through chlorophyll satellite imagery and flagged before people consume unsafe seafood. This shift from reactive to predictive health planning is what makes CSPH transformative.

From Risk Maps to Early Warnings

A second key component of CSPH is rigorous risk assessment. By quantifying exposure–response relationships, the framework shows how health risks rise with the intensity or frequency of hazards like heatwaves or floods. Vulnerability maps highlight communities most at risk, such as drought-prone villages far from food markets, enabling governments to target interventions more precisely. Building on this, CSPH emphasizes early warning systems that can provide lead times of weeks or months before disasters strike. Advances in climate forecasting already allow predictions of El Niño and La Niña up to 18 months ahead, offering a powerful tool for anticipating crop failures and food insecurity. In Madagascar, the Ministry of Fisheries is preparing to issue real-time alerts for harmful algal blooms through radio and social media, a departure from the past reliance on late, blanket warnings. Artificial intelligence adds another layer, with reinforcement learning being tested to recommend optimal policy responses under limited resources, whether to surge hospital staff during heatwaves, deploy food aid ahead of drought, or issue advisories about dangerous air quality.

Resilient Health Systems for a Changing Climate

The final pillar of CSPH extends beyond data and forecasting to the physical and human infrastructure of health care. It calls for climate-smart hospitals and clinics designed to withstand floods, cyclones, and power failures while running on renewable energy to ensure continuity of care. Adaptive features such as temperature regulation, clean water, and backup power systems are highlighted as essential safeguards. Equally important is training health professionals to recognize and treat climate-aggravated illnesses, from heat stress and respiratory disorders to the shifting patterns of malaria and dengue. Embedding climate knowledge in medical curricula and continuing education is seen as vital for preparing health workers to handle tomorrow’s challenges. In doing so, CSPH envisions health systems that are not only reactive to crises but proactive in preventing them, ensuring resilience at both community and institutional levels.

Towards a Global Model of Climate-Smart Public Health

Madagascar’s long history of climate-health engagement, with vulnerability assessments dating back to 2011, provides the foundation for this effort. Yet progress has often been slowed by limited resources, shortages of skilled workers, and fragmented systems. CSPH seeks to overcome these hurdles while aligning with international commitments such as the COP26 pledge to build climate-resilient health systems. Because the framework builds on District Health Information Software 2 (DHIS2), already used in more than 100 countries covering 40 percent of the world’s population, it has global scalability baked in. The algorithms and methods developed in Madagascar can be rapidly transferred to other nations, with Nepal already partnering to adapt the approach. Crucially, the researchers stress that success depends on co-production with local partners and the integration of indigenous knowledge, which has historically played a role in forecasting weather and predicting disease. Challenges remain, from uneven data quality to limited digital infrastructure, but the framework represents a leap toward uniting science, technology, and community engagement in the fight against climate-driven health crises.

Ultimately, CSPH is presented not as an optional innovation but as a necessity. Climate change will continue to intensify pressures on public health, and without integrated action, the human toll will be devastating. By combining modern data science with local engagement, CSPH offers a pathway to resilience, giving societies a chance not only to withstand the shocks of a warming world but also to adapt and thrive despite them.