Join Professor Joshua Tebbs of the University of South Carolina as he discusses how researchers in Iowa are using a Data Science technique to identify chlamydia. Group testing, also known as “pooled testing,” is a widely used method to screen for sexually transmitted diseases. Group testing estimates are used when the disease is rare because many individuals can be classied as disease-free when a single group tests negative. But historically, estimating a population-level prevalence of disease with a single group can be inaccurate and unrealistic. Tebbs will talk about his research using a Bayesian framework where researchers can more accurately identify chlamydia and other infectious diseases in group testing by drawing from broader datasets.