Ending millions of preventable deaths through more equitable, effective health systems in communities around the world

Computers on wrists can track steps and heart rates 24/7, yet in recent years more than five million mothers and children die annually from preventable causes — largely because they are excluded from or underserved by current health systems. In 2015, when countries aligned on Sustainable Development Goal (SDG) targets for health, they placed reducing the deaths of mothers and children at the top of their list. Between now and 2030, 12 million additional lives hang in the balance if these targets are not met.

The Rockefeller Foundation has a long history in health—from eradicating hookworm in the American South, to launching the field of public health, to seeding the development of the life-saving yellow fever vaccine. We continue to support innovative strategies that incentivize individuals, communities, governments, and funders to extend the benefits of good health and well-being to all, including the most vulnerable.

Today, the evidence is clear that community health can save lives, and that breakthroughs in data science have created new opportunities to transform traditional industries and sectors with cutting-edge data analytics, artificial intelligence, and machine learning. We believe the integration of disparate data sources and the application of advanced data science could reveal to key decision makers where and when to most effectively and equitably deploy scarce resources before health threats within communities become untenable.

We believe partnerships to build unified, data-driven insights are the key to unlocking the potential of community health– empowering decision-makers to identify and respond to health risks with a level of precision that will accelerate the world’s progress towards achieving health for all. Our current portfolio of work focuses on harnessing the power of data to connect mothers and children in hard to reach communities to quality health care.

The Latest

See All »