In a study published last week in “Nature Medicine,” a group of researchers from the Scripps Research Translational Institute discovered that wearable fitness devices may improve public health efforts to control the coronavirus.
The data analyzed was collected in the DETECT study, which was launched on March 25. The smartphone app gathers activity tracker and smartwatch data from consenting participants. It also collects the participants’ self-reported symptoms as well as diagnostic test results. Any adult living in the United States can participate in the study; all you have to do is download the MyDataHelps app.
The team noted that devices such as the Fitbit are able to identify coronavirus cases by simply assessing an individual’s heart rate, changes in sleep and activity levels and self-reported symptoms. Founder and director of the Scripps Research Translational Institute Eric Topol states that with about 100 million Americans already in possession of a smartwatch or wearable tracker, all that’s left is getting a small fraction of them — he estimated 2% — to use the app. This will allow the researchers to use the data to contain emerging outbreaks.
The data collected from the app will also allow researchers to note when participants deviate from their normal range for resting heart rate, activity level or sleep, as these deviations may be a sign of an infection or viral illness.
The question: How will researchers know if the illness behind these changes is COVID-19? To answer this, the researchers analyzed data from participants who were tested for the coronavirus or had reported developing symptoms of the viral infection. Knowing the results of the tests allowed the researchers to identify any specific changes that may indicate a COVID infection or other ailments.
The first author of the study, Giorgio Quer, explained that one of the biggest challenges in stopping the novel coronavirus infection from spreading was the ability to quickly pick out, track down and isolate infected persons. He notes that identifying individuals who may be asymptomatic or presymptomatic would be valuable, as individuals are likely to be more infectious during this period.
The study, which used data from wearable devices, could pinpoint with an 80% accuracy whether an individual had COVID-19. Significant factors that were considered in predicting the infection included less activity and more sleep. Study lead Jennifer Radin states that because common screening practices for COVID-19 may miss asymptomatic or presymptomatic cases, enrolling more participants in the research — she noted more than 100,000 individuals — would help researchers improve their predictions of individuals, including asymptomatic people, who will get sick.
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