Your Apple Watch May Know You Have Coronavirus Before You Do
Scientists discovered the surprising results using the Apple Watch’s Heart Rate Variability feature
N.B. This piece was originally written as part of an assessment for my MSc Science Communication course, pitched as a potential The Verge article.
Apple Watches can detect individuals with coronavirus and even predict a positive diagnosis up to seven days before an official swab, according to a new study by New York-based researchers. The results of the study, which is the first of its kind, suggest that the already popular watch (which 35% of US iPhone users have) could provide another way to effectively detect coronavirus infections. The “Warrior Watch Study” was carried out by scientists at the Icahn School of Medicine at Mount Sinai and used the Apple Watch’s Heart Rate Variability (HRV) measurement feature and other selfreported symptoms to uncover their surprising findings.
The research involved 297 participants, all of whom worked in the Mount Sinai Health System. Each person had an iPhone (series 6 or above), an Apple Watch (series 4 or above) and had to download the Warrior Watch App for the duration of the study between April and September 2020. Each day, participants wore their Apple Watch and entered any symptoms they were experiencing (like fever, fatigue or loss of smell or taste) and coronavirus test results into the study’s app.
The Apple Watches used in the study recorded HRV which is a measure of the variation in time (in milliseconds) between the wearer’s heartbeats. The scientists focused on HRV as it cycles throughout the day in a wave-like pattern (with high and low readings) and changes in this pattern (specifically consistently low HRV readings) could suggest a person has an infection.
The researchers discovered that participants with coronavirus who displayed symptoms (symptomatic) and those who were infected but showed no symptoms (asymptomatic) both had smaller HRV wave patterns (suggesting consistently lower HRV readings) than healthy individuals. What’s more, they found that these smaller waves started seven days before a person received a positive official coronavirus test result. So, not only did the Apple Watch predict infections, it detected participants with asymptomatic coronavirus infections — an infection type that has been hard to track and has contributed to the current challenge of containing the pandemic according to the study’s scientists.
Commenting on the results in an interview with CBS, Robert P. Hirten, MD, Assistant Professor of Medicine (Gastroenterology) at the Icahn School of Medicine at Mount Sinai, the study’s corresponding author said:
“Right now, we rely on people saying they’re sick and not feeling well but wearing an Apple Watch doesn’t require any active user input and can identify people who might be asymptomatic. It’s a way to better control infectious diseases.”
Using wearable tech like Apple Watches to help monitor infectious diseases has other advantages too as the study’s co-author Dr Zahi Fayad points out:
“This technology allows us not only to track and predict health outcomes, but also to intervene in a timely and remote manner, which is essential during a pandemic that requires people to stay apart.”
Despite its promising results, the scientists urge further study to better understand the usefulness of HRV data in detecting infectious diseases like coronavirus. The “Warrior Watch Study” hasn’t finished yet though. The researchers will next try to determine which healthcare workers are most at risk of psychological impacts from the pandemic by examining Apple Watch data including HRV, sleeping patterns and physical activity levels.
One thing is for sure, the study “highlights the future of digital health” according to Dr Hirten. Looking at both Apple’s recent sales data which shows 7.6 million Apple Watches were shipped in the first quarter of 2020 and its most recent Apple Watch Series 6 advert which ends with: “The future of health is on your wrist”, it certainly seems Apple shares the sentiment.
