Your wearable fitness tracker may help distinguish COVID-19 from flu

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In a new study, researchers analyzed heart rate, step count, and symptom duration in patients with flu and those with COVID-19 using Fitbit data and self-reported symptoms

While both showed similar-looking spikes in resting heart rate and decreases in average step count, COVID-19 symptoms lasted longer and peaked later.

The research was conducted by a team from Evidation Health.

Contrasting and comparing flu and COVID-19 is important for COVID-19 screening, as current practices often only check for more general symptoms like fever.

The study was conducted using Evidation’s app and network, Achievement—a connected cohort comprised of over 4 million individuals nationwide.

The findings confirmed that certain other symptoms are characteristic of COVID but not flu, like shortness of breath and coughing.

The team also examined the impact of each illness on decreasing daily step count, finding that the impacts lasted much longer for COVID than for flu.

For example, they used step count to measure a change in mobility and found that compared to their baseline, the number of steps didn’t go back to normal for people with COVID, even after three or four weeks.

This result, as well as reports of long-term fatigue, also hinted at the existence of chronic COVID cases, which had not yet been studied closely at the beginning of the pandemic when this data was gathered.

While data from wearables such as Fitbit can reveal a lot about these respiratory illnesses, the researchers maintain that it should be used as a general screening method, not a complete diagnostic tool.

The team says there’s potential to use wearable sensors and smartphones as high frequency/low-sensitive tests to shorten the time of detection and awareness of a possible ongoing infection.

It’s not a magic bullet, but if people can isolate themselves one or two days earlier than current standard testing procedures allow, that’s the most important thing because infectivity is highest around when symptoms first appear in symptomatic cases.

One author of the study is Luca Foschini, co-founder of Evidation Health.

The study is published in Patterns.

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