The pressures shaping health systems are increasingly global, but their effects are deeply local. While advances in data and technology are creating new opportunities to sense risk earlier, their impact depends on how effectively they respond to local realities, from infrastructure and workforce capacity to access and community needs.
This is especially important for prevention. Conditions that could often be detected or managed earlier are still identified too late, reducing treatment options, increasing costs, and leading to poorer outcomes for patients and health systems alike. Improving prevention requires more than better technology. It requires solutions that can turn early insight into timely action within the environments where people actually receive care.
Announced at the 79th World Health Assembly in Geneva, the winners of the Future Health Challenge 2026: Building Anticipatory Health Systems through Population Sensing demonstrate a growing global effort to make detection, prevention and proactive care more accessible. Selected from 393 submissions across 68 countries, the winning teams were recognised for solutions that strengthen early detection, improve understanding of population health, and support more effective system-level decision-making.
- ThinkMD, Winner
In many underserved communities, access to quality care depends heavily on frontline providers such as nurses, pharmacists and community health workers, often operating with limited training or diagnostic support. ThinkMD strengthens these frontline interactions through an offline clinical guidance platform that supports more consistent decision-making while generating real-time population health insights. By functioning in low-connectivity environments and aligning with local clinical protocols, the solution helps expand access to earlier detection and more reliable care. - Vector Control Innovations – VectorCam, Distinguished Finalist
In many malaria-endemic regions, access to entomological expertise and timely surveillance data is concentrated in urban centres, leaving some of the highest-risk communities underrepresented in national decision-making. Designed for low- resource environments, VectorCam enables community health workers to collect real-time mosquito surveillance data using offline AI tools. By shifting surveillance closer to the community level, the solution helps health authorities identify local transmission risks earlier and target interventions more equitably and effectively.
- Huna – Huna Cancer Navigator, Distinguished Finalist
Developed within Brazil’s multilayered healthcare landscape, Huna uses routine blood test data already generated by health systems to identify people at elevated risk of cancer without requiring new infrastructure or specialist diagnostics. By combining AI-powered triage with digital care coordination, the platform helps make existing screening pathways more targeted and accessible.
Together, these solutions reflect a growing global shift towards earlier detection, prevention and proactive care. While developed in very different healthcare environments, each demonstrates how locally grounded innovation can help health systems move from reacting to illness towards anticipating risk earlier, with benefits that can extend well beyond the geography of implementation.
Delivered by Future Health – A Global Initiative by Abu Dhabi, in collaboration with MIT Solve, the Challenge was designed to surface innovations that help to strengthen how early population-level signals are identified, interpreted and acted on, supporting earlier intervention and more effective allocation of resources.
At the heart of the Challenge is an expanded understanding of sensing itself. Early warning signals may come from a range of sources such as routine diagnostics, frontline consultations, community-level monitoring, environmental shifts or population trends. This broader view reflects an evolving approach to prevention, one that begins long before individuals engage with formal health services.
The range of solutions recognised at the World Health Assembly highlight how anticipatory healthcare can be adapted across different operating environments. What connects them is a shared focus on making insight usable, drawing from different types of locally available data and embedding insight within existing models of care, rather than imposing one-size- fits-all approaches. This approach helps build systems that are more responsive, prevention- oriented, and better equipped to support specific population needs.
Taken together, the winners of the Future Health Challenge 2026: Building Anticipatory Health Systems through Population Sensing showcase an emerging global consensus towards supporting better prediction, prevention, and timely action. By adapting to local needs while addressing shared global pressures, these solutions demonstrate how health systems around the world can move from reaction to readiness.
The challenge now is to continue learning from how these approaches are applied, refined and scaled across varied settings, to support healthier and more resilient populations worldwide.
Through Future Health, the selected innovators will engage with policymakers, investors, and health leaders ahead of the Abu Dhabi Future Health Summit from 20 to 22 October 2026, supporting the next phase of development, collaboration, and adoption.