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AI Health Virtual Seminar: Design and Implementation of a Novel Platform for COVID-19 Contact Tracing and Testing

Presented by:
Andrew Olson, MPP; Associate Director, Policy Strategy and Solutions for Health Data Science, Duke AI Health

In July, 2020, just a few months into the COVID-19 pandemic, the CDC funded the Snowball study to test an approach for more efficiently identifying and contacting people in Durham, NC who may be at risk of infection. The study deployed respondent-driven sampling methods, in which individuals infected with COVID-19 serve as seed cases and recruit their own social contacts for testing and enrollment in the study. To operationalize this approach, we built a cloud-based platform that integrates with the Duke Health electronic health record for case ascertainment and with the Research Electronic Data Capture (REDCap) application for electronic consent and collection of a social contact survey. The platform generates unique coupons that participants validate to enroll in the study and that are used to track all of the links between seeds and multiple waves of peer participants. The Snowball study tested novel methods of contact tracing as well as conducting clinical research and in this seminar we will describe the design of the platform and share results from the study.

 

Please join us for this afternoon virtual seminar. The presentation will be accessible to a broad audience, including those with no prior background in health data science or artificial intelligence.

Apr 12, 2023 04:00 PM in Eastern Time (US and Canada)