Mathematical and Computational Modeling Core for Global Infectious Disease Research
Official title: Mathematical, Computational, and Predictive Modeling Core
Funded at University of Vermont & St Agric College · NIH-11406283 · Data updated 2026-11-12
A core group at the University of Vermont helps researchers use math and computer models to understand and fight global infectious diseases like COVID-19.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Vermont & St Agric College NIH-funded |
| Lab location | 1 site (Burlington, United States) |
| Project start | September 15, 2018 |
| Project end | July 31, 2028 |
| Funding year | 2026 |
| Award (this year) | $201,113 |
| NIH project number | 5P20GM125498-09 |
| Project ID | NIH-11406283 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable to patients directly; this is a research core for scientists studying infectious diseases.
✕Less likely to help
Direct patient participation is unlikely; the grant supports modeling and collaboration rather than clinical trials.
What this research studies
This grant funds a modeling core that partners with researchers to translate complex biological data into predictive models. It aims to bridge gaps between biology and computation so that predictions about disease spread, antimicrobial resistance, vaccines, and diagnostics can guide real-world decisions. The core provides expertise, collaboration, and training to build strong, data-driven projects focused on global infectious diseases. Participation could involve researchers contributing data, validating models, and using results to inform public health strategies.
Why it matters
Potential benefit: If successful, the work could improve how we predict disease outbreaks and evaluate interventions, potentially guiding faster and better public health responses.
How similar studies have gone: Previous phases showed progress in bridging biomedical and computational disciplines and improving modeling collaboration.
Where this research is happening
-
University of Vermont & St Agric College
Burlington, United States Active
Researchers
- Principal investigator: Hébert-Dufresne, Laurent — University of Vermont & St Agric College
- Study coordinator: Hébert-Dufresne, Laurent
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.