Center to speed up AI-powered infectious disease research
Official title: Center for Transformative Infectious Disease Research (CTIDR)
Funded at Cornell University · NIH-11421473 · Data updated 2026-11-12
A Cornell-led center is using artificial intelligence to connect weather, ecosystems, and human health data to build usable models that predict infectious disease risks after extreme weather events.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Cornell University NIH-funded |
| Lab location | 1 site (Ithaca, United States) |
| Project start | September 17, 2024 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $295,548 |
| NIH project number | 5P20AI186093-03 |
| Project ID | NIH-11421473 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include communities in regions prone to extreme weather and researchers or clinicians who work with infectious disease data and predictive modeling.
✕Less likely to help
Individuals not involved in data collection or not located in affected regions may not experience direct benefits.
What this research studies
This grant funds a Living Evidence and Applied Data Modeling Core (LEAD-MC) to break down silos between fields like weather science, animal and human health, and policy analysis. The center will integrate diverse datasets and provide modeling expertise so researchers can build predictive epidemiological models that reflect real-world conditions. The goal is to create tools and capacity for transdisciplinary collaboration that can translate data into actionable insights for preventing disease after extreme weather. Participation would help researchers generate generalizable models that can be adapted to different locations and scenarios.
Why it matters
Potential benefit: If successful, patients and communities could receive better risk forecasts and timely public health guidance after extreme weather events.
How similar studies have gone: Previous efforts have shown that integrating multidisciplinary data improves predictive power for infectious disease risk, though this specific transdisciplinary LEAD-MC approach is novel.
Where this research is happening
-
Cornell University
Ithaca, United States Active
Researchers
- Principal investigator: Hayden, Alistair — Cornell University
- Study coordinator: Hayden, Alistair
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.