Software for analyzing health data trends over time
Official title: Software for Geostatistical Smoothing and Joinpoint Regression Modeling of Time Series of Compositional Variables in Epidemiology
Funded at Biomedware · NIH-10915851 · Data updated 2026-11-12
This study is creating a new software tool to help researchers and public health officials better understand cancer trends over time and predict future health challenges by analyzing health data in a clear and helpful way.
Quick facts
| Grant type | Sbir 1 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Biomedware NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project start | June 5, 2024 |
| Project end | November 30, 2025 |
| Funding year | 2024 |
| Award (this year) | $295,861 |
| NIH project number | 1R43ES035667-01A1 |
| Project ID | NIH-10915851 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals involved in cancer epidemiology, including researchers and public health professionals who analyze health data.
✕Less likely to help
Patients who are not engaged in research or public health analysis may not directly benefit from this software development.
What this research studies
This research focuses on developing innovative software that utilizes geostatistical methods to analyze time series data related to health outcomes, particularly in cancer epidemiology. By employing joinpoint regression, the software aims to identify changes in health trends and project future disease burdens. It will model complex data that includes percentages and proportions, ensuring that the results are coherent and meaningful. The software will also address the challenges of analyzing spatial variations in health data, providing a comprehensive tool for researchers and public health officials.
Why it matters
Potential benefit: If successful, this research could enhance the accuracy of health trend analyses, leading to better understanding and management of cancer epidemiology.
How similar studies have gone: While the approach of using geostatistical methods in health data analysis is established, the specific software being developed is novel and aims to fill a gap in current methodologies.
Where this research is happening
-
Biomedware
Ann Arbor, United States Active
Researchers
- Principal investigator: Goovaerts, Pierre E — Biomedware
- Study coordinator: Goovaerts, Pierre E
Related research
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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.