Understanding genetic diversity in mosquito populations in sub-Saharan Africa
Official title: Computational Population Genetics
Funded at University of Oregon · NIH-11000286 · Data updated 2026-11-12
This study is looking at the genetic information of malaria-carrying mosquitoes to understand how they adapt to control efforts, which could help us find better ways to manage and reduce malaria in Africa.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Oregon NIH-funded |
| Lab location | 1 site (Eugene, United States) |
| Project start | February 7, 2023 |
| Project end | December 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $323,934 |
| NIH project number | 5R35GM148253-03 |
| Project ID | NIH-11000286 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for participation or benefit from this research include individuals living in sub-Saharan Africa who are affected by malaria or are involved in vector control efforts.
✕Less likely to help
Patients who do not reside in sub-Saharan Africa or are not affected by malaria may not receive direct benefits from this research.
What this research studies
This research focuses on analyzing the vast amounts of genomic data generated from mosquito populations, particularly Anopheles gambiae, which are key vectors for malaria in sub-Saharan Africa. By employing advanced computational methods, including deep learning, the project aims to develop new analytical techniques that can better interpret the genetic variations and evolutionary responses of these mosquitoes to control measures. The goal is to enhance our understanding of how these populations adapt and evolve, which could inform more effective vector control strategies.
Why it matters
Potential benefit: If successful, this research could lead to improved strategies for controlling malaria transmission by understanding mosquito genetics and evolution.
How similar studies have gone: Previous research using similar computational approaches has shown promise in understanding genetic diversity and evolution in other species, suggesting potential success for this novel application.
Where this research is happening
-
University of Oregon
Eugene, United States Active
Researchers
- Principal investigator: Kern, Andrew D — University of Oregon
- Study coordinator: Kern, Andrew D
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.