Google Earth AI is being developed to make global public health more proactive by weaving local health data into geospatial models, aiming to cut reporting lags, forecast outbreaks, and better guide care for vulnerable communities.

The approach blends environmental signals, satellite imagery, mobility data, and foundation models—AlphaEarth Foundations and the Population Dynamics Foundation Model—through a Geospatial Reasoning agent to reveal how people interact with their environments.

Two research prototypes, the Geospatial Reasoning agent and the planetary prediction engine, enable plain-language, autonomous disease forecasting and conversational spatial mapping for frontline teams.

PDFM (Population Dynamics Foundation Model) aggregates search trends, mobility, and environmental data to deliver high-resolution, dynamic health insights that can be integrated into researchers’ systems.

Public health workflow is supported by PDFM embeddings as Population Dynamics Insights, with no-cost access for select use cases and Google Earth credits for eligible noncommercial professionals.

The narrative emphasizes shifting from reactive to proactive health management through data-driven tools and collaboration with global health partners.

Google.org funded INRB to modernize testing and surveillance infrastructure, highlighting a broader commitment to global health capacity building.

Impact examples include cardiovascular mortality forecasting at NYU Langone Health, cross-border immunization tracking at Mount Sinai and Boston Children’s Hospital, dengue outbreak forecasting across Mexico with Oxford and Tecnológico de Monterrey, and cholera hotspot prediction in the DRC with WHO AFRO.

During the Ebola outbreak in the Democratic Republic of Congo, WHO AFRO and DRC’s INRB used prototypes to identify transmission blind spots and at-risk populations, and to simulate outbreak trajectories to improve planning and response timelines.

The initiative integrates practical workflows for public health with accessible AI tools and geospatial capabilities, supporting frontline decision-making.

Overall, the effort represents a move toward proactive, data-driven public health through advanced analytics and international collaboration.