USDA employs AI-driven models to target screwworm outbreaks and prevent resurgence

USDA researchers are using predictive modelling and AI to strengthen surveillance and control of New World screwworm in the US. The tools aim to identify high-risk areas and guide more targeted sterile-fly releases and other interventions.

New cases of New World screwworm in the United States have sharpened attention on how the pest moves, and where it is most likely to strike next. USDA researchers are using predictive models and artificial intelligence to steer surveillance, sterile-fly releases and other interventions more precisely.

According to the Agricultural Research Service, the models combine ecological suitability, weather patterns and outbreak history to identify landscapes where the parasite could establish itself and the routes it may follow. Dr Scott Hutchins, USDA’s undersecretary for research, education and economics, said precision intervention is now central to pest control, while Kim Lohmeyer, who leads the ARS laboratory in Kerrville, Texas, described the forecasting tools as a “game-changer”.

The approach is designed to strengthen the Sterile Insect Technique, a method USDA says helped eradicate screwworm from the US in 1966 and contained a Florida Keys outbreak in 2017. The agency is also developing male-only strains, including NovoFly, to improve the efficiency of future releases.

Officials stressed that the models cannot anticipate every scenario, particularly when infested animals are moved by people. Livestock owners have been urged to report suspected cases quickly and avoid transporting affected animals.