Fitness tracker biometrics predicts COVID-19 better than temperatures

According to new research, temperature controls, increasingly denigrated as COVID theater, can be overcome as an indicator of illness by fitness tracker biometrics and self-reported symptoms.

Of particular interest were changes in an individual’s historical and contemporary resting heart rate and normal sleep duration in identifying presymptomatic and asymptomatic individuals. Step counting also played a role in the diagnosis.

Those who have been infected are more likely to see their heart rate increase, sometimes faster than 100 beats per minute, rather than having a fever.

Combining these deviations with self-reported symptoms allowed the researchers to more accurately distinguish the difference between volunteers who were symptomatic and COVID-19 positive and those who were not.

Nearly 31,000 people from all 50 states have signed up. Of these, 3,811 reported symptoms. Fifty-four symptomatic volunteers reported being positive; 279 were negative.

Although supported by a relatively small sample of volunteers, the result is significant. There is still no better way to combat the spread of the coronavirus than to identify infections, trace contacts, and quarantine symptomatic and asymptomatic COVID-19 individuals.

Demand for rapid one-time COVID-19 antigen tests still continues to exceed availability in the United States. And people in unrestricted contact areas should be tested on an ongoing basis until the infection rate drops dramatically and permanently because they interact with more people.

To see if a new option can be found, a biometric app – MyDataHelps – was created by a team of researchers from the Scripps Research Translational Institute and CareEvolution, which runs HIEBus, a technology platform for exchanging health information.

A fitness tracker information exchange, called Detect or Digital Engagement and Tracking for Early Control and Treatment, was launched in March. Data collected by Fitbit, Apple’s HealthKit and Google’s Fit devices was uploaded to Detect and shared among researchers.

Topics of the article

biometric data | biometrics | biometric research | data collection | fitness monitoring | heartbeat | temperature monitoring | Wearable