Integrating real-world data to better predict respiratory disease spread
Official title: Integrating opportunistic data into respiratory disease models to enhance surveillance, explain seasonality, and reveal spatial transmission landscapes
Funded at Georgetown University · NIH-11401097 · Data updated 2026-11-12
A research team at Georgetown University is using real-world data to build models that better predict how respiratory diseases spread over time and across places, helping policymakers and clinicians plan better responses.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Georgetown University NIH-funded |
| Lab location | 1 site (Washington, United States) |
| Project start | May 1, 2024 |
| Project end | April 30, 2029 |
| Funding year | 2026 |
| Award (this year) | $426,660 |
| NIH project number | 5R35GM153478-03 |
| Project ID | NIH-11401097 on NIH RePORTER |
Who could benefit from this research
✓Could help
No direct patient enrollment is described; the study analyzes population-level data and models of disease spread.
✕Less likely to help
No patient participation is described for this grant as stated.
What this research studies
This project combines health data, social factors, and environment to create models that capture how people’s behavior and surroundings influence disease spread. The team develops both generative and inferential models to understand how behavior, transmission, and interventions interact at multiple scales. The work aims to fill gaps in behavioral surveillance and improve forecasting of where and when outbreaks may occur. It leverages opportunistic data to illuminate spatial transmission patterns and seasonality to support smarter public health decisions.
Why it matters
Potential benefit: If successful, the work could lead to more accurate outbreak forecasts and better-informed intervention choices that protect communities.
How similar studies have gone: Previous work shows that incorporating socio-behavioral factors can improve epidemic forecasts, though integrating opportunistic data at scale is still being developed.
Where this research is happening
-
Georgetown University
Washington, United States Active
Researchers
- Principal investigator: Bansal, Shweta — Georgetown University
- Study coordinator: Bansal, Shweta
Related research
Other NIH-funded projects on the same topics.
-
Household air pollution and child DNA changes tied to later lung health
A study in Guatemalan children looks at how early exposure to smoky kitchen fuel changes DNA and could influence respiratory health as they grow.
-
Genetic testing and specialist care for rare causes of chronic lung, sinus, and ear infections
This project offers stepwise genetic testing and specialty referrals to find rare inherited causes of recurring lung, sinus, and ear infections in children and adults.
-
Quantitative imaging to find chronic lung disease in high-risk patients
A project will use advanced chest CT image analysis to detect chronic lung diseases early in veterans, aiming to help people who might otherwise go undiagnosed.
-
Understanding lung diseases by combining genetic data and big biobank information
A big research project will look at genes, health data, and other biological information from diverse people to better understand why COPD and asthma develop and vary across populations.
-
Early-life household air pollution and DNA changes linked to childhood respiratory health in Guatemalan kids
This study looks at how exposure to smoke from solid fuel at home in early life may affect DNA and respiratory health in Guatemalan children enrolled in the HAPIN trial.
-
Long-term endotypes of prematurity-related lung disease in former preemies
A long-term study looking at why some babies born very early develop lasting breathing problems and how their genes might explain these different paths.
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.