Improving infection control and prevention using advanced modeling techniques
RFA-CK20-003: Modeling of infectious network dynamics for surveillance, control and prevention enhancement (MINDSCAPE)
This study is working on smart tools to help doctors better understand and predict infections that can happen in hospitals, like MRSA and C. diff, so they can take quicker action to keep patients safe.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Francisco NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-11031915 on NIH RePORTER |
What this research studies
This research focuses on using mathematical modeling and machine learning to enhance the understanding and prediction of healthcare-associated infections (HAI) and antimicrobial-resistant infections (ARI). By developing decision-making technologies that provide real-time feedback to healthcare providers, the project aims to improve risk assessment and control measures for infections like methicillin-resistant Staphylococcus aureus and Clostridioides difficile. The research team, composed of experts from various fields, will utilize clinical, microbiological, and environmental data to continuously adapt their models to changing epidemiological conditions.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients receiving care in healthcare settings where HAIs and ARIs are prevalent.
Not a fit: Patients who are not currently receiving treatment in healthcare facilities or those without risk factors for HAIs and ARIs may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly reduce the incidence of healthcare-associated infections and improve patient safety.
How similar studies have performed: Previous research has shown that mathematical modeling and machine learning can effectively inform infection control strategies, indicating a promising approach in this area.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Porco, Travis Christian — University of California, San Francisco
- Study coordinator: Porco, Travis Christian
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 below.