Abstract:

Infectious disease testing frequently takes advantage of two tools — group testing and multiplex assays — to make testing timely and cost effective. Until the work of Tebbs et al. (Biometrics, 2013) and Hou et al. (Biometrics, 2017), there was no research available to understand how best to apply these tools simultaneously. This recent work focused on applications where each individual is considered to be identical in terms of the probability of disease. But, what if individual risk-factor information, such as past behavior and presence of symptoms, was somehow included in the testing process? The purpose of this presentation is to propose the first group testing algorithms for multiplex assays that can take advantage of individual risk-factor information as expressed by these probabilities. These new algorithms significantly reduce the expected number of tests required while preserving accuracy. Throughout this presentation, focus is on applying these new algorithms with the Aptima Combo 2 Assay that is used worldwide for chlamydia and gonorrhea screening.

This research is supported by Grant R01 AI121351 from the National Institutes of Health.