East Africa is testing a new technology that identifies locations of previously unknown mosquito breeding habitats and treats them within the same day.

The technology involves a smartphone app that pairs an algorithm with a drone and satellite data using geospatial artificial intelligence to identify locations of previously unknown mosquito breeding habitats, for treatment.

Christened ‘Seek and Destroy’, the programme has been in trial in Uganda, and will be expanded to infectious areas in Kenya and Rwanda in East Africa and in Cambodia, allowing governments to quickly and efficiently direct resources to vulnerable areas before disease outbreaks can occur.

Developed by a University of South Florida public health researcher and associate professor, Benjamin Jacob, it is hoped the technology will be used by insect control agencies to monitor real time, map and eradicate the malaria vectors and larvae.

Most of the research thus far has been focused in Uganda, where malaria is the leading cause of death, especially among children under five.

A low-cost (< $1000) drone (DJI Phantom) was employed for eco-geographically locating, water bodies including natural water bodies, irrigated rice paddies, cultivated swamps, ditches, ponds, and other geo-locations, which are among the common breeding sites for Anopheles mosquitoes in Gulu district of Northern Uganda.

The system works by identifying specific environments and organisms by their unique “fingerprint”, mapping and assigning a red-green-blue value associated exclusively with a species or habitat.

‘Seek and Destroy’

For ‘Seek and Destroy’ to be successful, Jacob trained the drone to sense and capture image datasets through his algorithms that allow the system to understand key features, like mud or vegetation, based on their ‘fingerprints’.

Each image is then processed and gridded with identified sources of water on those surfaces.

The data is then classified into different categories based on the presence or absence of mosquito larvae and whether the water is positive for mosquitoes.

Paired with Jacob’s algorithms, the drone was 100 percent accurate in locating bodies of water where mosquitoes are most likely to breed.

“We real time retrieved each georeferenced sentinel site signature which was subsequently archived in the drone dashboard spectral library using the smartphone app. Each georeferenced, UAV-sensed, capture point was inspected using a mobile field team including trained local village residents led by a vector control officer on the same day the habitats were geo-AI signature mapped, spatially forecasted and treated,” he explained.

The American Journal of Entomology says Jacob discovered that each of the 120 homes he studied was infested with at least 200 mosquitoes. With the help of the local insect control officers he trained, Jacob destroyed 100 percent of identified habitats in 31 days.