Temperature data collected by wearable devices worn on the finger are often reliably used to detect the onset of fevers, a number one symptom of both COVID-19 & the flu, consistent with a team of researchers from the University of California San Diego, UC San Francisco & MIT Lincoln Lab.
Researchers published their analysis in a paper titled “Feasibility of continuous fever monitoring using wearable devices” in the December 14 issue of the journal Scientific Reports. They emphasize that the study is a proof of the concept effort with data from only 50 participants reporting COVID-19.
The Scientific Reports paper is the first published result from TemPredict, a study of more than 65000 people wearing ring manufactured by Finnish startup Oura that records temperature, pulse, rate of respiration & levels of activity. The goal of the study is to develop an algorithm which will predict the onset of symptoms like fever, cough & fatigue, which are characteristic of COVID-19. Researchers said, they hope to succeed in that goal by the end of the year. They also hope the algorithms will allow public health officials to act faster to contain the virus spread.
“This is not just a science problem, it is a social problem,” said Benjamin Smarr, the paper’s corresponding author & a professor in the Department of Bioengineering and the Halicioglu Data Sciences Institute at UC San Diego. “With wearable devices which will measure temperature, we will begin to envision a public COVID early alert system.”
But users from diverse-backgrounds would need to feel safe sharing their data for such efforts to actually work, Smarr added. The data is stripped of all personal information including location, and every subject is understood by a random identifying number.
Smarr is TemPredict’s data analytics lead. Ashley Mason, a professor in the Department of Psychiatry & the Osher Center for Integrative Medicine at UC San Francisco, is the principal investigator of the study.
“If wearables allow us to detect COVID-19 early, people can begin physical isolation practices and acquire testing to reduce the spread of virus,” Mason said. In this way, an ounce of prevention could be worth even more than a pound of cure.”
Wearables like the Oura ring collect temperature data continuously throughout the day & night allowing researchers to measure people’s true temperature baselines and identify fever peaks more accurately. “Temperature varies not only from person-to-person but also for the same person at different times of the day,” Smarr said.
The study, he explains, highlights of the importance of collecting data continuously over long periods of time. Incidentally, the lack of continuous data is also why temperature spot checks aren’t effective for detecting COVID-19. These spot checks are the equivalent of catching a syllable per minute during a conversation, instead of whole sentences, Smarr said.
In the Scientific Reports paper, Smarr & colleagues noticed that fever onset often happened before subjects were reporting symptoms, and even to those that never reported other symptoms. “It supports the hypothesis that some fever like events may go unreported or unnoticed without being truly asymptomatic,” the researchers write. “Wearables therefore may contribute to identifying rates of asymptomatic illness as against unreported illness of special importance in the COVID-19 pandemic.”
The 50 subjects in the study all owned Oura rings and had COVID-19 before joining TemPredict. They provided symptom summaries for their illnesses and gave researchers access to the data, their Oura rings had collected during the period once they were sick. The signal for fever onset wasn’t subtle, Smarr said. “The chart tracking people who had a fever seemed like it was on fire.”
The data collected as a part of the next TemPredict study included 65000 subjects, and these data are going to be stored at the San Diego Supercomputer Center at UC San Diego, where a team led by Ilkay Altintas is building a portal to enable other researchers to access these data for other analysis.
“The data collected has a great potential to be linked with other datasets making individual & societal scale models be combined to further understand the disease,” said Ilkay Altintas, the chief data science officer at the San Diego Supercomputer Center. The better we will make to share the data & optimize the utilization of it through digital technologies, the quicker other researchers will make use of it in their studies.”
“We got to make sure that our algorithms work for everyone ,” Smarr said.