How Earth observation data can transform public health

For decades, public health has operated on a reactive model, responding to the onset of symptoms and the arrival of patients at healthcare facilities. However, this model—already under considerable strain and subject to clear limitations—is proving increasingly inadequate as climate, environmental, and public health crises cease to be exceptional events and instead become part of our new normal.

Climate and environmental phenomena such as heatwaves, air pollution, floods, droughts, and shifts in the distribution of disease vectors have a direct and measurable impact on population health. They significantly increase the risk of respiratory, cardiovascular, and infectious diseases, as well as mental health disorders. Despite this, these early warning signals remain largely absent from formal public health decision-making processes.

This is precisely where Earth observation, through satellite data combined with advanced analytics and artificial intelligence, can spark a decisive paradigm shift. By enabling the continuous monitoring of critical environmental variables—such as air pollution, surface temperature, humidity, vegetation, and the extent of water bodies—these data, together with increasingly accurate weather forecasts, provide an early view of emerging risk factors. This makes it possible to identify patterns, trends, and anomalies that precede health impacts, helping societies anticipate, prepare for, and mitigate their consequences rather than simply reacting to them.

The international projects in which GMV participates and plays a leading role prove that this approach is far more than a theoretical concept and is steadily advancing toward operational implementation. Two notable examples are “EO4Health Resilience,” which demonstrates how Earth observation data can be used to anticipate risks associated with vector-borne and waterborne diseases, and “AIR4HEALTH,” which explores the integration of air quality and environmental data with health information to support risk assessment and enable more informed decisions regarding population exposure to air pollution.

The challenge, therefore, is no longer primarily technological. Instead, it is fundamentally institutional and cultural. Integrating environmental data into public health decision-making requires breaking down sectoral silos, fostering collaboration across scientific communities, and recognizing that prevention begins long before people come into contact with the healthcare system. It also means acknowledging that investing in anticipation is, ultimately, an investment in resilience and in our societies’ capacity to respond effectively to future challenges.

In a world where climate and environmental pressures are bound to intensify, sticking to a purely reactive approach means accepting increasingly severe and unsustainable human, social and economic costs. Earth observation data provide an opportunity to take a broader, more integrated, and preventive approach to public health.

The question, therefore, is no longer whether we should use these data, but how quickly we can integrate them effectively into the decisions that shape population health.

Author: Filipe Brandão