Adaptive Disease Surveillance – Center for Health Decision Science

Gregg Gonsalves discussed using adaptive approaches to improve infectious disease surveillance at a recent CHDS seminar. Gonsalves, an Associate Professor at Yale School of Public Health and an adjunct Associate Professor at Yale Law School, discussed the development and deployment of tools to help geographically target infectious disease surveillance to increase the number of diagnosed cases. By increasing the number of diagnosed cases, individuals with an infection can be treated more rapidly and chains of transmission can be halted. These tools use adaptive techniques like Thompson sampling and profile likelihood sampling to identify where testing resources should be focused – unlike static strategies where testing might be solely focused on initially selected areas (e.g., places known to have many high risk individuals), these adaptive strategies switch which areas are targeted for testing in response to new information.

Gonsalves discussed these approaches in the context of both HIV and SARS-CoV-2 testing – he presented simulation studies showing when these targeting methods perform better than non-adaptive approaches. He also presented results from a pilot study conducted in Columbus, OH, that used Thompson sampling to guide the location of SARS-CoV-2 testing sites, and discussed future work deploying a similar strategy in New York City.

Learn more: Read the publication, An Adaptive Approach to Locating Mobile HIV Testing Services
Learn more: Read the publication, Surveillance for endemic infectious disease outbreaks: Adaptive sampling using profile likelihood estimation