How human movement and behavior shape infectious disease spread
Official title: Novel data and approaches for dynamic modeling of human behavior and infectious disease ecology
Funded at University of California Berkeley · NIH-11196221 · Data updated 2026-11-12
This project builds computer models that link people's contacts, movement, and protective actions to how infections spread so communities can better target prevention.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Berkeley NIH-funded |
| Lab location | 1 site (Berkeley, United States) |
| Project start | September 24, 2024 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $400,751 |
| NIH project number | 5R35GM156856-02 |
| Project ID | NIH-11196221 on NIH RePORTER |
Who could benefit from this research
✓Could help
People living in communities affected by communicable diseases or who can contribute anonymized mobility or survey data would be most relevant to this work.
✕Less likely to help
Patients with conditions unrelated to infectious disease or those not represented in the social or digital data (for example, people without mobile phones) may not see direct benefit.
What this research studies
The team will combine data such as mobile-phone movement, demographic records, and surveys to create computer models that connect how people interact with how diseases move. Models will include differences across neighborhoods, age groups, and time, and allow people's behaviors to change in response to outbreaks. By including feedback between disease levels and human behavior, the work aims to explain why some groups face higher risk and how interventions might alter that risk. Most analyses use anonymous, population-level data rather than individual clinic visits.
Why it matters
Potential benefit: If successful, this work could help public-health officials design more effective, targeted interventions that reduce infections and narrow disparities in risk.
How similar studies have gone: Previous models using mobility and behavior data have improved outbreak forecasts, but jointly modeling two-way feedback between behavior and disease across diverse populations is a newer and less-tested approach.
Where this research is happening
-
University of California Berkeley
Berkeley, United States Active
Researchers
- Principal investigator: Mahmud, Ayesha Sanchita — University of California Berkeley
- Study coordinator: Mahmud, Ayesha Sanchita
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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.