Think you’ve recovered fully from COVID-19? Your Fitbit may say otherwise, Scripps Research reports

If you’ve had COVID-19 and are wondering why, months later, you don’t feel like your old self, the answer might be wrapped around your wrist, according to a study by La Jolla-based Scripps Research.

Scripps scientists sifted through wearable-device data in an effort to understand how COVID-19 infections affect heart rate, sleep and activity levels. They found it typically takes two to three months for those measures to return to pre-COVID levels. But in some people, those changes drag on much longer, and researchers are only beginning to understand why.

The study findings, published July 7 in the scientific journal JAMA Network Open, indicate that the road to recovery is longer and harder for COVID-19 than for other respiratory infections. Researchers say monitoring wearable gadgets for telltale signs that someone is sick has a variety of uses, from encouraging people to get tested and seek medical care to helping officials spot emerging outbreaks.

“No one’s really done this before,” said Jennifer Radin, an epidemiologist at Scripps Research and leader of the study. “It definitely, objectively gives evidence that what people are experiencing can be measured with these devices.”

It’s the latest example of researchers mining this ever-growing treasure trove of data. One in five Americans owns a wearable device such as a Fitbit or Apple Watch. The gadgets monitor things such as how fast your heart’s thumping and your feet are running and how often you toss and turn at night.

“If you’re able to really characterize what’s normal for each person, then you can identify these more subtle changes that may indicate they’re coming down with a viral illness,” Radin said.

She cites heart rate as an example. The American Heart Association says a healthy adult’s resting heart rate can vary from 60 to 100 beats per minute, but no one person’s pulse varies that drastically. A smaller jump from, say, 60 to 75, could be an early indicator that something is amiss.

Detecting such subtle signs is the goal of Scripps’ ongoing DETECT study (Digital Engagement & Tracking for Early Control & Treatment). Participants share their data by downloading the MyDataHelps app on the App Store or Google Play. Names and other personal identifying information are removed before researchers look at the data.

Between March 2020 and January, more than 37,000 people enrolled in the study. Of those, 875 participants who had respiratory infections were tested for COVID-19, with 234 testing positive.

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Scientists at Scripps Research in La Jolla found that data from wearable devices coupled with self-reported symptoms help predict whether someone has the virus.

Radin’s team found that those with COVID-19 tended to sleep longer and were less active than study participants with other respiratory infections. Their heart rates differed, too, dipping below pre-infection levels about a week after symptoms started and then shooting up.

The heart rate pattern was a surprise, Radin said, and suggests that the disease affects the part of the nervous system that controls pulse and other bodily functions we don’t think about consciously.

“It’s still a hypothesis,” she said. “We don’t know exactly why this is occurring, and that’s something we hope to better understand.”

It took about two to three months for most people’s data to return to pre-infection levels. But in about 14 percent of cases, heart rates stayed higher than normal for more than four months. Researchers found that those volunteers tended to have had worse symptoms during the initial phase of the disease, such as body aches and trouble breathing.

That may mean that a bad initial bout of disease increases the risk of long COVID, a poorly understood condition that can leave some people with chest pain, shortness of breath and trouble thinking clearly for months.

Going forward, the research team plans to use data from wearable devices to understand how people respond to COVID-19 vaccines.

Researchers also are planning a study in San Diego to see whether wearable-device data can predict changes in the number of COVID- and influenza-like infections reported by the county. They hope to enroll 7,000 to 10,000 participants and show that their data can predict outbreaks and whether current public health strategies are working.

The DETECT study is continuing. To learn more, visit detectstudy.org. ◆