BUCHS, Switzerland – Can fertility trace bracelets used by women to help achieve pregnancy also be helpful for health-oriented men? According to a new study, one such portable device can also indicate COVID-19 infection as early as 48 hours before symptoms develop!
The fertility tracker by Ava, which claims to be the first FDA-approved, can reduce the spread of COVID-19 by acting as an early warning system. Carried like a watch, it helps women get pregnant by identifying the most promising days in their menstrual cycle. Information is based on skin temperature, pulse rate, blood flow, sleep patterns, breathing and heart rate, before being sent to a smartphone application.
The same measurements also detect initial signs of coronavirus, such as fever, scientists say. Corresponding author Dr Lorenz Risch and colleagues predicted nearly 70 percent of cases up to two days in advance.
“To our knowledge, this is the first prospective study to measure physiological changes in respiratory rate, heart rate, skin temperature and perfusion to develop an algorithm to detect pre-symptomatic COVID-19 infection,” the authors write in their paper.
These patients are likely to ignore safety precautions, leading to increased virus transmission. Early isolation will limit contact with susceptible individuals.
The findings are based on 1,163 adults under 50 in Liechtenstein, which were detected between March 2020 and April 2021. Participants wore the bracelet at night. It stores data every 10 seconds and requires at least four hours of relatively uninterrupted sleep. Devices were synchronized with a complementary smartphone application that recorded alcohol consumption, prescription or recreational drugs, and possible COVID symptoms.
Regular rapid antibody tests for the virus were also undertaken. Those with an indication of symptoms also took a PCR swab test. All provided personal information about age, gender, smoking status, blood type, number of children, exposure to household contacts or work colleagues who tested positive for COVID, and vaccination status.
About 127 people (11 percent) developed the infection, 66 of whom wore their bracelet for at least 29 days before the onset of symptoms. They were confirmed as positive by PCR swab test, so were included in the final analysis. The monitoring data revealed significant changes in all five physiological indicators. COVID symptoms lasted an average of 8.5 days.
The algorithm was “trained” using 70 percent of the data from day 10 to day two before the onset of symptoms within a 40-day period of continuous monitoring of the 66 people who tested positive. It was then tested on the remaining 30 percent. About 73 percent of the laboratory-confirmed positive cases were picked up in the training set and 68 percent in the test set up to two days before the onset of symptoms.
“Portable sensor technology can enable Covid-19 detection during the pre-symptomatic period. Our proposed algorithm identified 68% of COVID-19 positive participants two days before the onset of symptoms, ”the authors concluded.
It is now being tested in a much larger group of 20,000 people in the Netherlands. Results are expected later this year.
“Recent studies have highlighted the need to identify potential cases before the onset of symptoms to prevent virus transmission. Our findings suggest that a portable-informed machine learning algorithm could serve as a promising tool for pre-symptomatic or asymptomatic detection of COVID-19, “the paper reads.
The Ava Fertility Tracker is a device that detects the fertile days in your cycle, and takes some of the guesswork out of the process.
“Portable sensor technology is an easy-to-use, low-cost method to enable individuals to track their health and well-being during a pandemic,” the authors say. “Our research shows how these devices, in conjunction with artificial intelligence, can push the boundaries of personalized medicine and detect diseases before symptoms occur, potentially reducing virus transmission in communities.”
The research is published in the journal BMJ open.
Suidwes News Service author Mark Waghorn contributed to this post.