Earlier Predictions in COVID-19 Infection Rates With Wearable Device Data and CareEvolution’s Research Platform

ANN ARBOR, Mich.–(BUSINESS WIRE)–New research enabled by CareEvolution’s research platform indicates commercially available wearable devices show promise for monitoring and forecasting population changes in COVID-19 activity and infection rates up to 12 days earlier than CDC data alone. This approach of using wearable devices for monitoring infection rates complements existing methods for tracking viral illnesses, including medical appointments, laboratory test results, and wastewater testing by providing an early signal for changes in disease prevalence.

These data come from DETECT, a collaborative study launched at the onset of the COVID-19 pandemic by Scripps Research in partnership with CareEvolution and The Rockefeller Foundation. The study utilizes CareEvolution’s digital clinical trial and research platform, MyDataHelps™, through which researchers collected resting heart rate and step count from wearable devices and self-reported data (e.g., test results, symptoms, and demographic information) from thousands of participants across the United States.

On September 22, Lancet Digital Health published a study based on DETECT data, showing that wearables can identify variations in individual data, perhaps before the participant experiences any symptoms, providing an early indication of viral infection. The researchers showed that tracking changes in this sensor data can significantly improve predictions for the seven-day moving average of COVID-19 infection rates up to 12 days in the future when compared to CDC data alone.

“Passive, continuous monitoring through wearables can unlock a deeper understanding of population-level early physiological responses to viruses,” says co-author Edward Ramos, Ph.D., Principal Science Officer at CareEvolution and co-founder of the Digital Trials Center at Scripps Research. “With the ever-increasing prevalence of fitness trackers or smart watches, there’s potential to not only enhance the surveillance of COVID-19 infection, but the onset of other viral respiratory illnesses as well.”

Relative to other data collections intended for viral illness tracking, such as wastewater testing, sensor-based surveillance provides inexpensive data that complement these traditional monitoring tactics, giving a population-level prediction of viral infection trends. Integrating sensor-based data with traditional surveillance methods could be critical for developing actionable insights for future COVID-19 predictions, other emerging viruses, and seasonal epidemics.

About DETECT

The DETECT study was launched on March 25, 2020, and is open to any adult (aged ≥18 years) living in the USA who has a Fitbit or a smartwatch or fitness tracker that connects to Apple HealthKit or Google Fit. Participants join the study by downloading the MyDataHelps™ app, which is available on Android and iPhone operating systems. Learn more about the DETECT study.

Funding for the study includes support in part from the National Center for Advancing Translational Sciences of the US National Institutes of Health, The Rockefeller Foundation, and Amazon Web Services.

About CareEvolution

CareEvolution is a health technology company headquartered in Ann Arbor. The organization has partnered with research teams across the country, including University of Massachusetts Chan Medical School, University of Michigan, the National Institutes of Health, and Scripps Research Digital Trials Center. These partners leverage MyDataHelps™ for projects such as the All of Us Research Program, RECOVER, PowerMom, Say Yes! COVID Test, and the electronic Framingham Heart Study, with nearly 2 million mHealth participants, over 55k EHRs connected and over 20 million kits distributed to participants across the United States.

Contacts

Leah Judge

[email protected]