Measuring how public-health actions change infectious disease spread
Observational causal inference with infectious disease outcomes
This project develops better ways to measure how real-world public-health actions change the spread of infectious diseases like HIV and COVID-19 so communities and decision-makers have more reliable information.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brown University NIH-funded |
| Lab location | 1 site (Providence, United States) |
| Project ID | NIH-11190829 on NIH RePORTER |
What this research studies
From a patient perspective, researchers are building statistical tools that use real-world data to understand how interventions such as vaccines, treatments, or social measures affect disease spread. They will adapt and improve observational methods (like difference-in-differences and synthetic controls) so they work correctly when infections grow or decline nonlinearly. The team will test their methods using simulated outbreaks and past public-health data to check for bias and improve how findings can be applied to new places. The goal is to make projections from real-world data more realistic and useful for planning responses that protect communities.
Who could benefit from this research
Good fit: Ideal candidates for benefiting from this work include people and communities affected by infectious diseases such as HIV or COVID-19, public-health agencies, and clinicians who rely on better estimates to plan interventions.
Not a fit: Patients with conditions unrelated to infectious diseases or those needing immediate individual medical treatment are unlikely to receive direct benefit from this methodological project.
Why it matters
Potential benefit: If successful, this work could provide more accurate, trustworthy estimates of how public-health actions reduce infections, helping policymakers design safer, more effective responses that protect patients and communities.
How similar studies have performed: Related observational methods have worked well for linear policy outcomes, but applying them reliably to infectious disease transmission is newer and more challenging.
Where this research is happening
Providence, United States
- Brown University — Providence, United States (Active)
Researchers
- Principal investigator: Bilinski, Alyssa — Brown University
- Study coordinator: Bilinski, Alyssa
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.