AI-powered smart traps to monitor malaria-carrying mosquitoes in Africa
Official title: Area B Transmission
Funded at University of Florida · NIH-11507594 · Data updated 2026-11-12
A large NIH grant funds the development of AI-driven traps and fast identification tools to help track and control malaria-carrying mosquitoes in sub-Saharan Africa, with potential benefits for children and communities at risk.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | April 22, 2024 |
| Project end | March 31, 2029 |
| Funding year | 2026 |
| Award (this year) | $65,357 |
| NIH project number | 3U19AI181594-03S2 |
| Project ID | NIH-11507594 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are residents of sub-Saharan Africa and communities in areas with malaria transmission, as well as field-working epidemiologists and vector-control personnel.
✕Less likely to help
Communities without exposure to malaria risks or where interventions are not yet deployed may not directly benefit.
What this research studies
This program project focuses on understanding how Anopheles stephensi and other malaria vectors behave, spread, and develop resistance to insecticides in Nigeria, Cameroon, and other parts of Sub-Saharan Africa. Researchers will create field-ready tools, including MALDI-MS for species and resistance detection and smart AI-driven traps to monitor mosquitoes in real time. The work aims to improve early warning and targeted control to reduce malaria risk for people living in endemic areas. All activities are designed to inform public health actions and vector-control efforts that could directly affect communities, including families with young children.
Why it matters
Potential benefit: If successful, the project could reduce malaria transmission by enabling faster detection and smarter vector control in at-risk communities.
How similar studies have gone: Previous work has shown AI-driven traps can improve mosquito surveillance, but deploying field-ready MALDI-MS and smart traps in Africa is a novel and ambitious step.
Where this research is happening
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University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Dinglasan, Rhoel David Ramos — University of Florida
- Study coordinator: Dinglasan, Rhoel David Ramos
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.