How infectious diseases can be driven to elimination
Modeling the dynamics of disease elimination
Researchers will build computer models using real-world infection data to show how diseases like COVID-19, MRSA, and trachoma can be driven to elimination to help public health teams and communities.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| 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-11171731 on NIH RePORTER |
What this research studies
You will learn how scientists use large health databases and computer models to figure out what it takes to stop infections from spreading. They combine information on vaccination, mass drug campaigns, and antibiotic use to simulate transmission and the effects of different interventions. The work focuses on situations where each infected person infects fewer than one other person and looks at factors like super-spreaders and pockets of low immunity in communities. The goal is to produce practical modeling tools public health teams can use to plan and target elimination efforts.
Who could benefit from this research
Good fit: People affected by or living in communities at risk for communicable diseases such as COVID-19, MRSA, or neglected tropical infections, or those willing to share health-related data, would be most relevant to this work.
Not a fit: People with no exposure or risk to the studied communicable diseases or those unwilling to share any health information are unlikely to receive direct benefit from this modeling project.
Why it matters
Potential benefit: If successful, this work could guide smarter vaccination, treatment, and public-health campaigns that reduce infections and help eliminate specific diseases in communities.
How similar studies have performed: Mathematical models have successfully guided vaccination and elimination campaigns in past outbreaks, but applying models to brink-of-elimination scenarios that include real-world heterogeneity is a newer and still-developing approach.
Where this research is happening
San Francisco, United States
- University of California, San Francisco — San Francisco, United States (Active)
Researchers
- Principal investigator: Blumberg, Seth — University of California, San Francisco
- Study coordinator: Blumberg, Seth
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.