Community-driven model to reduce overdose deaths through smarter resource use
Official title: C-DIAS RP 1: A community-driven modeling approach for identifying and implementing evidence-based interventions and implementation strategies to reduce overdose deaths.
Funded at Stanford University · NIH-11626449 · Data updated 2026-11-12
A Stanford-led project uses a data-driven model to help counties pick the best ways to prevent opioid and stimulant overdoses and save lives.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | August 1, 2022 |
| Project end | May 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $315,113 |
| NIH project number | 3P50DA054072-05S1 |
| Project ID | NIH-11626449 on NIH RePORTER |
Who could benefit from this research
✓Could help
This grant is not a patient-facing trial; it focuses on community and county-level strategies to prevent overdoses.
✕Less likely to help
Direct patient participation in a clinical sense is not described; benefits arise from better-informed public health decisions.
What this research studies
This project will build a model-driven decision support system that helps counties prioritize and optimize how they use resources to reduce overdose deaths. It will combine administrative, interview, and survey data with a modular agent-based model to test different implementation strategies in realistic, changing contexts. A ongoing community-research partnership will ensure findings are locally relevant and trustworthy for decision makers. The work aims to identify robust strategies that adapt to varying county needs and capacities, guiding future actions and funding decisions.
Why it matters
Potential benefit: If successful, communities could use the tool to choose the most effective, context-specific interventions to lower overdose deaths and improve emergency care outcomes.
How similar studies have gone: Previous data-driven approaches have informed public health strategies, but this model adds a local-context, implementation-focused angle and agent-based simulations.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Brown, C. Hendricks — Stanford University
- Study coordinator: Brown, C. Hendricks
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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.