Predicting and understanding the spread of antibiotic-resistant bacteria in hospitals and communities
Official title: Utilizing phylodynamic and causal artificial intelligence methods for predicting and characterizing antibiotic resistant bacterial transmission within and beyond hospital settings
Funded at University of Florida · NIH-11066691 · Data updated 2026-11-12
This study is looking at how antibiotic-resistant infections spread in hospitals by using smart technology and genetic information, with the goal of finding better ways to keep patients safe and healthy.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | January 1, 2025 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $43,131 |
| NIH project number | 1F30AI183562-01A1 |
| Project ID | NIH-11066691 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include patients who are hospitalized or have recently been treated for infections caused by antibiotic-resistant bacteria.
✕Less likely to help
Patients with infections that are not caused by antibiotic-resistant bacteria may not receive direct benefits from this research.
What this research studies
This research aims to tackle the growing problem of antibiotic resistance, especially in hospital settings, by using advanced artificial intelligence and genomic methods. It will analyze complex data from various sources, including genetic information of bacteria and patient health records, to better understand how antibiotic-resistant infections spread. By identifying transmission patterns, the research seeks to improve infection control measures and ultimately enhance patient safety. Patients may benefit from improved strategies to prevent and manage antibiotic-resistant infections.
Why it matters
Potential benefit: If successful, this research could lead to more effective prevention and treatment strategies for antibiotic-resistant infections, improving patient outcomes.
How similar studies have gone: Previous research has shown promise in using genomic and AI methods to track and control antibiotic-resistant infections, indicating that this approach could be effective.
Where this research is happening
-
University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Cohen, Scott a — University of Florida
- Study coordinator: Cohen, Scott a
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.