The Agricultural Research Service (ARS) is using predictive modeling and artificial intelligence to help identify where New World screwworm (NWS) infestations could emerge and spread in the U.S. The models analyze ecological, environmental and historical data, including habitat suitability, temperature, precipitation, host preferences and previous outbreaks. The information helps agencies identify areas at increased risk and strategically direct surveillance, fly trapping, personnel, aircraft and sterile insects.
“Modeling their movement and using this information for optimal placement maximizes our impact and hastens eradication,” said Scott Hutchins, USDA undersecretary for research, education and economics. ARS developed the models to help guide surveillance and determine where and when to implement the sterile insect technique. This proven technique involves releasing sterile flies into areas where NWS is present or likely to spread, disrupting the pest’s reproductive cycle.
Kim Lohmeyer, director of the ARS Knipling-Bushland Livestock Insects Research Laboratory in Kerrville, TX, said predictive modeling provides a “forewarning system” to help guide surveillance and management decisions. However, the models cannot account for every scenario, including unpredictable events such as people transporting infested animals. Therefore, producers are encouraged to work with state animal health officials and follow all requirements for moving livestock into or out of infested areas.
Currently, there are two active cases in the U.S., one in Texas and one in New Mexico. Both cases are in horses. For more information on NWS, visit www.screwworm.gov.