Smartwatches can track COVID-19 symptoms, study finds
University of Michigan researchers found that new signals embedded in heart rate indicated when individuals were infected with COVID-19 and how ill they became.
If a COVID-19 infection develops, a wearable device may eventually be able to clue you in. A study at the University of Michigan found that a smartwatch can monitor how symptoms progress.
The study evaluated the effects of COVID-19 with various factors derived from heart-rate data. This method also could be employed to detect other diseases, such as influenza and the common cold, at home or when medical resources are limited, such as during a pandemic or in developing countries.
Tracking students and medical interns across the country, the University of Michigan researchers found that new signals embedded in heart rate indicated when individuals were infected with COVID-19 and how ill they became.
For instance, they discovered that individuals with COVID-19 experienced an increase in heart rate per step after the onset of their symptoms. Meanwhile, people who reported a cough as one of their COVID-19 symptoms had a much more elevated heart rate per step than those without a cough.
“We previously developed a variety of algorithms to analyze data from wearable devices. So, when the COVID-19 pandemic hit, it was only natural to apply some of these algorithms to see if we can get a better understanding of disease progression,” says Caleb Mayer, a doctoral student in mathematics at the University of Michigan and a co-first author of the study.
People may not internally sense COVID-19’s direct impact on the heart, but “heart rate is a vital sign that gives a picture of overall health," says Daniel Forger, a University of Michigan professor.
Millions of people are tracking their heart rate through wearable devices. This information is already generating a tremendous amount of data for researchers to analyze, says co-author Daniel Forger, professor of mathematics and research professor of computational medicine and bioinformatics at the University of Michigan.
“Heart rate is affected by many different physiological signals,” Forger explains. “For instance, if your lungs aren’t functioning properly, your heart may need to beat faster to meet metabolic demands. Your heart rate has a natural daily rhythm governed by internal biological clocks.” While people may not internally sense COVID-19’s direct impact on the heart, he adds that “heart rate is a vital sign that gives a picture of overall health.”
Among the total of 2,164 participants who enrolled in the student study, 72 undergraduate and graduate students contracted COVID-19, providing wearable data from 50 days before symptom onset to 14 days after. The researchers also analyzed this type of data for 43 medical interns from the Intern Health Study by the Michigan Neuroscience Institute and 29 individuals (who are not affiliated with the university) from the publicly available dataset.
Participants could wear the device on either wrist. They also documented their COVID-19 symptoms, such as fever, shortness of breath, cough, runny nose, vomiting, diarrhea, body aches, loss of taste, loss of smell, and sore throat.
Experts not involved in the study found the research to be productive. “This work is pioneering and reveals exciting new insights into the many important ways that we can derive clinically significant information about disease progression from consumer-grade wearable devices,” says Lisa A. Marsch, director of the Center for Technology and Behavioral Health and a professor in the Geisel School of Medicine at Dartmouth College. “Heart-rate data are among the highest-quality data that can be obtained via wearables.”
Beyond the heart, she adds, “Wearable devices are providing novel insights into individuals’ physiology and behavior in many health domains.” In particular, “this study beautifully illustrates how digital-health methodologies can markedly enhance our understanding of differences in individuals’ experience with disease and health.”
Previous studies had demonstrated that COVID-19 affects cardiovascular functions. Capitalizing on this knowledge, the University of Michigan endeavor took “a giant step forward,” says Gisele Oda, a researcher at the Institute of Biosciences at the University of Sao Paulo in Brazil and an expert in chronobiology—the science of biological rhythms. She commends the researchers for developing a complex algorithm that “could extract useful information beyond the established knowledge that heart rate increases and becomes more irregular in COVID patients.”
Wearable devices open the possibility of obtaining large-scale, long, continuous, and real-time heart-rate data on people performing everyday activities or while sleeping. “Importantly, the conceptual basis of this algorithm put circadian rhythms at the center stage,” Oda says, referring to the physical, mental, and behavioral changes that follow a 24-hour cycle. “What we knew before was often based on short-time heart rate measured at any time of day,” she adds, while noting that heart rate varies between day and night and also changes with activity.
However, without comparison to a control group of people having the common flu, it is difficult to determine if the heart-rate signals are unique to COVID-19 or also occur with other illnesses, says John Torous, an assistant professor of psychiatry at Harvard Medical School who has researched wearable devices. In addition, he points to recent data showing that many wearables, which work by beaming light through the skin, may be less accurate in people with darker skin due to variations in light absorption.
While the results sound interesting, they lack the level of conclusive evidence that would be needed to transform how physicians care for patients. “But it is a good step in learning more about what these wearables can tell us,” says Torous, who is also director of digital psychiatry at Beth Israel Deaconess Medical Center, a Harvard affiliate, in Boston. A follow-up step would entail replicating the results in a different pool of people to “help us realize the full value of this work.”
It is important to note that this research was conducted in university settings during the early phases of the pandemic, with remote learning in full swing amid strict isolation and quarantine mandates in effect. The findings demonstrate that physiological monitoring can be performed using consumer-grade wearable sensors, allowing research to continue without in-person contact, says Sung Won Choi, a professor of pediatrics at the University of Michigan who is principal investigator of the student study.
“The worldwide COVID-19 pandemic interrupted a lot of activities that relied on face-to-face interactions, including clinical research,” Choi says. “Mobile technology proved to be tremendously beneficial during that time, because it allowed us to collect detailed physiological data from research participants remotely over an entire semester.” In fact, the researchers did not have any in-person contact with the students involved in the study. “Everything was done virtually," Choi explains. "Importantly, their willingness to participate in research and share data during this historical time, combined with the capacity of secure cloud storage and novel mathematical analytics, enabled our research teams to identify unique patterns in heart-rate data associated with COVID-19.”
Dr. Steffanie Strathdee, an infectious disease epidemiologist, saved her husband Tom from a superbug infection by mobilizing scientists around the world to help him access experimental phage therapy.
[Editor's Note: This is the fifth episode in our Moonshot series, which explores cutting-edge scientific developments that stand to fundamentally transform our world.]
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
The latest tools, like whole genome sequencing, are allowing food outbreaks to be identified and stopped more quickly.
With the pandemic at the forefront of everyone's minds, many people have wondered if food could be a source of coronavirus transmission. Luckily, that "seems unlikely," according to the CDC, but foodborne illnesses do still sicken a whopping 48 million people per year.
Whole genome sequencing is like "going from an eight-bit image—maybe like what you would see in Minecraft—to a high definition image."
In normal times, when there isn't a historic global health crisis infecting millions and affecting the lives of billions, foodborne outbreaks are real and frightening, potentially deadly, and can cause widespread fear of particular foods. Think of Romaine lettuce spreading E. coli last year— an outbreak that infected more than 500 people and killed eight—or peanut butter spreading salmonella in 2008, which infected 167 people.
The technologies available to detect and prevent the next foodborne disease outbreak have improved greatly over the past 30-plus years, particularly during the past decade, and better, more nimble technologies are being developed, according to experts in government, academia, and private industry. The key to advancing detection of harmful foodborne pathogens, they say, is increasing speed and portability of detection, and the precision of that detection.
Getting to Rapid Results
Researchers at Purdue University have recently developed a lateral flow assay that, with the help of a laser, can detect toxins and pathogenic E. coli. Lateral flow assays are cheap and easy to use; a good example is a home pregnancy test. You place a liquid or liquefied sample on a piece of paper designed to detect a single substance and soon after you get the results in the form of a colored line: yes or no.
"They're a great portable tool for us for food contaminant detection," says Carmen Gondhalekar, a fifth-year biomedical engineering graduate student at Purdue. "But one of the areas where paper-based lateral flow assays could use improvement is in multiplexing capability and their sensitivity."
J. Paul Robinson, a professor in Purdue's Colleges of Veterinary Medicine and Engineering, and Gondhalekar's advisor, agrees. "One of the fundamental problems that we have in detection is that it is hard to identify pathogens in complex samples," he says.
When it comes to foodborne disease outbreaks, you don't always know what substance you're looking for, so an assay made to detect only a single substance isn't always effective. The goal of the project at Purdue is to make assays that can detect multiple substances at once.
These assays would be more complex than a pregnancy test. As detailed in Gondhalekar's recent paper, a laser pulse helps create a spectral signal from the sample on the assay paper, and the spectral signal is then used to determine if any unique wavelengths associated with one of several toxins or pathogens are present in the sample. Though the handheld technology has yet to be built, the idea is that the results would be given on the spot. So someone in the field trying to track the source of a Salmonella infection could, for instance, put a suspected lettuce sample on the assay and see if it has the pathogen on it.
"What our technology is designed to do is to give you a rapid assessment of the sample," says Robinson. "The goal here is speed."
Seeing the Pathogen in "High-Def"
"One in six Americans will get a foodborne illness every year," according to Dr. Heather Carleton, a microbiologist at the Centers for Disease Control and Prevention's Enteric Diseases Laboratory Branch. But not every foodborne outbreak makes the news. In 2017 alone, the CDC monitored between 18 and 37 foodborne poison clusters per week and investigated 200 multi-state clusters. Hardboiled eggs, ground beef, chopped salad kits, raw oysters, frozen tuna, and pre-cut melon are just a taste of the foods that were investigated last year for different strains of listeria, salmonella, and E. coli.
At the heart of the CDC investigations is PulseNet, a national network of laboratories that uses DNA fingerprinting to detect outbreaks at local and regional levels. This is how it works: When a patient gets sick—with symptoms like vomiting and fever, for instance—they will go to a hospital or clinic for treatment. Since we're talking about foodborne illnesses, a clinician will likely take a stool sample from the patient and send it off to a laboratory to see if there is a foodborne pathogen, like salmonella, E. Coli, or another one. If it does contain a potentially harmful pathogen, then a bacterial isolate of that identified sample is sent to a regional public health lab so that whole genome sequencing can be performed.
Whole genome sequencing can differentiate "virtually all" strains of foodborne pathogens, no matter the species, according to the FDA.
Whole genome sequencing is a method for reading the entire genome of a bacterial isolate (or from any organism, for that matter). Instead of working with a couple dozen data points, now you're working with millions of base pairs. Carleton likes to describe it as "going from an eight-bit image—maybe like what you would see in Minecraft—to a high definition image," she says. "It's really an evolution of how we detect foodborne illnesses and identify outbreaks."
If the bacterial isolate matches another in the CDC's database, this means there could be a potential outbreak and an investigation may be started, with the goal of tracking the pathogen to its source.
Whole genome sequencing has been a relatively recent shift in foodborne disease detection. For more than 20 years, the standard technique for analyzing pathogens in foodborne disease outbreaks was pulsed-field gel electrophoresis. This method creates a DNA fingerprint for each sample in the form of a pattern of about 15-30 "bands," with each band representing a piece of DNA. Researchers like Carleton can use this fingerprint to see if two samples are from the same bacteria. The problem is that 15-30 bands are not enough to differentiate all isolates. Some isolates whose bands look very similar may actually come from different sources and some whose bands look different may be from the same source. But if you can see the entire DNA fingerprint, then you don't have that issue. That's where whole genome sequencing comes in.
Although the PulseNet team had piloted whole genome sequencing as early as 2013, it wasn't until July of last year that the transition to using whole genome sequencing for all pathogens was complete. Though whole genome sequencing requires far more computing power to generate, analyze, and compare those millions of data points, the payoff is huge.
Stopping Outbreaks Sooner
The U.S. Food and Drug Administration (FDA) acquired their first whole genome sequencers in 2008, according to Dr. Eric Brown, the Director of the Division of Microbiology in the FDA's Office of Regulatory Science. Since then, through their GenomeTrakr program, a network of more than 60 domestic and international labs, the FDA has sequenced and publicly shared more than 400,000 isolates. "The impact of what whole genome sequencing could do to resolve a foodborne outbreak event was no less impactful than when NASA turned on the Hubble Telescope for the first time," says Brown.
Whole genome sequencing has helped identify strains of Salmonella that prior methods were unable to differentiate. In fact, whole genome sequencing can differentiate "virtually all" strains of foodborne pathogens, no matter the species, according to the FDA. This means it takes fewer clinical cases—fewer sick people—to detect and end an outbreak.
And perhaps the largest benefit of whole genome sequencing is that these detailed sequences—the millions of base pairs—can imply geographic location. The genomic information of bacterial strains can be different depending on the area of the country, helping these public health agencies eventually track the source of outbreaks—a restaurant, a farm, a food-processing center.
Coming Soon: "Lab in a Backpack"
Now that whole genome sequencing has become the go-to technology of choice for analyzing foodborne pathogens, the next step is making the process nimbler and more portable. Putting "the lab in a backpack," as Brown says.
The CDC's Carleton agrees. "Right now, the sequencer we use is a fairly big box that weighs about 60 pounds," she says. "We can't take it into the field."
A company called Oxford Nanopore Technologies is developing handheld sequencers. Their devices are meant to "enable the sequencing of anything by anyone anywhere," according to Dan Turner, the VP of Applications at Oxford Nanopore.
"The sooner that we can see linkages…the sooner the FDA gets in action to mitigate the problem and put in some kind of preventative control."
"Right now, sequencing is very much something that is done by people in white coats in laboratories that are set up for that purpose," says Turner. Oxford Nanopore would like to create a new, democratized paradigm.
The FDA is currently testing these types of portable sequencers. "We're very excited about it. We've done some pilots, to be able to do that sequencing in the field. To actually do it at a pond, at a river, at a canal. To do it on site right there," says Brown. "This, of course, is huge because it means we can have real-time sequencing capability to stay in step with an actual laboratory investigation in the field."
"The timeliness of this information is critical," says Marc Allard, a senior biomedical research officer and Brown's colleague at the FDA. "The sooner that we can see linkages…the sooner the FDA gets in action to mitigate the problem and put in some kind of preventative control."
At the moment, the world is rightly focused on COVID-19. But as the danger of one virus subsides, it's only a matter of time before another pathogen strikes. Hopefully, with new and advancing technology like whole genome sequencing, we can stop the next deadly outbreak before it really gets going.