Understanding how interventions affect infectious disease outcomes
Official title: Observational causal inference with infectious disease outcomes
Funded at Brown University · NIH-10941031 · Data updated 2026-11-12
This study looks at how different treatments and vaccines can help control the spread of diseases like COVID-19 and HIV, using real-life data to see what works best, so we can make better predictions about future health measures.
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 start | September 15, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2024 |
| Award (this year) | $382,852 |
| NIH project number | 1R35GM155224-01 |
| Project ID | NIH-10941031 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals affected by infectious diseases such as COVID-19 or HIV, as well as those involved in public health interventions.
✕Less likely to help
Patients who are not affected by infectious diseases or who do not engage with public health interventions may not receive direct benefits from this research.
What this research studies
This research investigates how different interventions, such as vaccines and therapeutics, impact the spread of infectious diseases like COVID-19 and HIV. By using observational causal inference models, the project aims to analyze real-world data to provide more accurate estimates of intervention effectiveness. This approach compares outcomes in treated and untreated groups to better understand the true impact of various health measures. The goal is to improve the accuracy of predictions regarding how future interventions might affect disease transmission.
Why it matters
Potential benefit: If successful, this research could lead to more effective public health strategies and interventions for controlling infectious diseases.
How similar studies have gone: Other research has shown success with observational causal inference models in different contexts, suggesting potential for this approach in infectious disease outcomes.
Where this research is happening
-
Brown University
Providence, United States Active
Researchers
- Principal investigator: Bilinski, Alyssa — Brown University
- Study coordinator: Bilinski, Alyssa
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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.