Developing Predictive Models for COVID-19 with Wearables Data (2021-2022)

Background The COVID-19 pandemic has resulted in over nine million infections and over 229,000 deaths in the U.S. alone as of October 30, 2020. To quickly identify and isolate new infections and clusters, public health officials are seeking new tools to target diagnostic testing for individuals who exhibit symptoms. Previous research has demonstrated that wearable technologies can detect physiologic and behavioral changes when a user becomes infected with influenza, including a heightened resting heart rate, lower heart rate variability, decreased blood oxygen saturation, disturbed sleep, decreased physical activity and changes in wear habits. Together, these "digital biomarkers" form a signature of infection. In April 2020, Duke launched CovIdentify to test the viability of using wearables to quickly identify individuals who may have contracted the coronavirus. The CovIdentify platform integrates information from widely used wearables with simple daily electronic self-reports on symptoms and social distancing, for up to 12 months. CovIdentify's overarching objective is to implement existing digital biomarkers and establish new digital biomarkers to develop, validate and translate CovIdentify as a continuous screening tool. Since September 21, 2020, researchers have collected data from over 5,500 individuals. Project Description This project's three goals are to develop digital biomarkers associated with COVID-19, provide visualizations of these biomarkers for both participants and researchers, and recruit members of underrepresented groups through community outreach. With the development of a large-scale database housing REDCAP survey data, wearable device data and iOS application data, the next step for this project is data visualization and analysis. The team will create dashboards that visualize the digital biomarkers to provide participants with an understanding of their health and give other researchers the tools to develop their own digital biomarkers. In addition, since the project will continue to collect users' wearable and survey data, the team must ensure that the population is representative of the target population. Team members will continue the work with the Duke Clinical and Translational Science Institute (CTSI) Recruitment Innovation Center (RIC) to present to community groups (virtually) and deliver wearable devices to underrepresented groups through the approved in-person, contactless protocol. The team will pursue the following aims: Digital biomarker development: With the redesign of the database that stores wearable and survey data from participants into an efficient structure, team members will be able develop digital biomarkers. Dashboard development: The current iOS application can only pull data that is stored on a participant's Apple Health Kit. The team will pull each individual's data from the new database and display information in a simple yet informative manner. Community outreach: The team will not only seek to diversify the study population by improving the recruitment and outreach efforts but also provide ways to meet the needs of the community groups affected by COVID-19 Learn more about this project team by viewing the team's video. Anticipated Outputs Database system for storing, securing and retrieving study data; identification and validation of digital biomarkers; blog posts and publications