Using an integrated multimodal sensing system, Soumya Srivastava is developing a tool and a machine-learning algorithm to detect tick-borne diseases. Simply put, tick-borne infections can be detected on a single chip from a blood sample. Most existing tests can only identify infections up to six weeks after a tick bite. Srivastava’s tool aims to detect disease within one to two weeks.
“Tick-borne disease can lead to serious morbidity and mortality, and it has increased significantly in the last 15-20 years in the U.S.,” she said. “This project will create a rapid, sensitive and label-free diagnostic tool to improve early detection.”