Page 18 - Abacoa Community News - December '20

Page 18, Abacoa
science on the cuttinG edGe

The Scripps Research Institute News

Scripps Research DETECT changes in heart rate, sleep
and activity levels, along
Study Suggests Fitness with self-reported symptom
Trackers And Smartwatches data – and can identify cases
with greater success than
Can Predict COVID-19 looking at symptoms alone.

“What’s exciting here
Infection is that we now have a
validated digital signal for
Examining data from the first six weeks of their landmark COVID-19. The next step
DETECT study, a team of scientists from the Scripps Research is to use this to prevent Eric Topol
Translational Institute sees encouraging signs that wearable emerging outbreaks from improvement from other models that only evaluated self-
fitness devices can improve public health efforts to control spreading,” says Eric Topol, M.D., director and founder of reported symptoms.
COVID-19. the Scripps Research Translational Institute and executive As of June 7, 30,529 individuals had enrolled in the
The DETECT study, launched on March 25, uses a mobile vice president of Scripps Research. “Roughly 100 million study, with representation from every United States state.
app to collect smartwatch and activity tracker data from Americans already have a wearable tracker or smartwatch Of these, 3,811 reported symptoms, 54 tested positive for
consenting participants, and also gathers their self-reported and can help us; all we need is a tiny fraction of them – just 1 the coronavirus and 279 tested negative. More sleep and less
symptoms and diagnostic test results. Any adult living in percent or 2 percent – to use the app.” activity than an individual’s normal levels were significant
the United States is eligible to participate in the study by With data from the app, researchers can see when factors in predicting coronavirus infection.
downloading the research app, MyDataHelps. participants fall out of their normal range for sleep, activity The predictive model under development in DETECT
In a study published Oct. 29 in Nature Medicine, the level or resting heart rate; deviations from individual norms might someday help public health officials spot coronavirus
Scripps Research team reports that wearable devices like Fitbit are a sign of viral illness or infection. hotspots early. It also may encourage people who are potentially
are capable of identifying cases of COVID-19 by evaluating But how do they know if the illness causing those changes infected to immediately seek diagnostic testing and, if necessary,
is COVID-19? To answer that question, the team reviewed data quarantine themselves to avoid spreading the virus.
“We know that common screening practices for the
from those who reported developing symptoms and were tested

The Groove for the novel coronavirus. Knowing the test results enabled coronavirus can easily miss pre-symptomatic or asymptomatic
them to pinpoint specific changes indicative of COVID-19
cases,” says Jennifer Radin, Ph.D., an epidemiologist at the
Band Rocks versus other illnesses. Scripps Research Translational Institute who is leading the
“One of the greatest challenges in stopping COVID-19
study. “And infrequent viral tests, with often-delayed results,

from spreading is the ability to quickly identify, trace and
don’t offer the real-time insights we need to control the spread
The Courtyard isolate infected individuals,” says Giorgio Quer, Ph.D., director of the virus.”

The DETECT team is now actively recruiting more
of artificial intelligence at Scripps Research Translational
Institute and first author of the study. “Early identification of
participants for this important research. The goal to enroll more
those who are pre-symptomatic or even asymptomatic would than 100,000 people, which will help the scientists improve
Report and Photos be especially valuable, as people may potentially be even more their predictions of who will get sick, including those who are
by Penny Sheltz infectious during this period. That’s the ultimate goal.” asymptomatic. In addition, Radin and her colleagues plan to
The G roove For the study, the team used health data from fitness incorporate data from frontline essential workers who are at
Band performed wearables and other devices to identify – with roughly 80 an especially high risk of infection.
outside at percent prediction accuracy – whether a person who reported Learn more about joining the DETECT study at
Downtown at the symptoms was likely to have COVID-19. This is a significant detectstudy.org.
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