CovIdentify Dataset

This dataset supports the study "A method for intelligent allocation ofdiagnostic testing by leveraging data from commercial wearable devices: a casestudy on COVID-19," which developed an Intelligent Testing Allocation (ITA)method. The study demonstrated the efficacy of using continuous digitalbiomarkers like resting heart rate and steps to enhance COVID-19 diagnostictesting positivity rates. The findings suggest significant potential forlarge-scale, symptom-independent surveillance testing to alleviate diagnostictest shortages. The provided data is from the CovIdentify study launched byDuke's BIG IDEAs Lab in the Biomedical Engineering Department. From April 2nd,2020 to May 25th, 2021, 2,887 participants connected their smartwatches to theCovIdentify platform, including 1,689 Garmin, 1,091 Fitbit, and 107 Applesmartwatches