Improving disease mapping and boundary detection using advanced statistical methods
Official title: Bayesian Modeling and Inference for High-Dimensional Disease Mapping and Boundary Detection"
Funded at University of California Los Angeles · NIH-11009905 · Data updated 2026-11-12
This study is working on better ways to understand how cancer risk varies in different places, using smart statistical methods to help public health researchers make better decisions about prevention and treatment.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | February 1, 2023 |
| Project end | January 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $264,290 |
| NIH project number | 5R01GM148761-03 |
| Project ID | NIH-11009905 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals living in areas with varying cancer incidence rates who may benefit from improved public health strategies.
✕Less likely to help
Patients who do not reside in the study areas or do not have a relevant cancer diagnosis may not receive direct benefits from this research.
What this research studies
This research focuses on enhancing statistical techniques for mapping diseases and analyzing spatial boundaries, particularly for cancer. By utilizing Bayesian methods, the project aims to better understand geographic variations in disease risk and identify potential causes. It involves analyzing complex datasets that include multiple cancer types and various geographic and temporal factors. The goal is to provide public health researchers with improved tools to interpret data and make informed decisions.
Why it matters
Potential benefit: If successful, this research could lead to more accurate disease mapping, helping to identify at-risk populations and inform targeted interventions.
How similar studies have gone: Previous research has shown promise in using Bayesian methods for disease mapping, indicating that this approach could yield significant advancements.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Banerjee, Sudipto — University of California Los Angeles
- Study coordinator: Banerjee, Sudipto
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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.