A Fitbit might see when you get the flu – before the symptoms have even developed.
Researchers analyzed 60 days of data from 47,248 Fitbit users in the US to try to predict when they would fall ill.
Significant signs that someone was about to get sick were higher heart beats than normal or excessive sleep, both of which could be measured with the Fitbit.
The researchers said the breakthrough devices at home would allow earlier flu outbreaks to be predicted so that health officials could respond more quickly to control them.
A Fitbit-style device might recognize when you get the flu – before the symptoms have even developed (stock image)
Flu outbreaks can be fought by ensuring that people are vaccinated and encouraging patients to stay at home and wash their hands regularly.
Antiviral drugs can also be used to limit the virus. Measures of this kind could be taken sooner if doctors received early warning signs that the disease was spreading.
Fitbits are popular watch-like devices that users wear on their wrists to track their physical activity, heart rate and sleep pattern.
Study author Dr. Jennifer Radin of the Scripps Research Translational Institute in California said: “Faster response to influenza outbreaks can prevent further spread and infection, and we were curious if sensor data could improve real-time state-level surveillance.
“We demonstrate the potential of metrics from portable devices to improve flu monitoring and, consequently, to improve public health response.
“As these devices improve in the future and with access to 24/7 real-time data, it is possible to identify flu rates on a daily rather than a weekly basis.”
The study is surrounded by flu outbreaks in the UK and the US, which have added extra pressure to hospitals that are already overwhelmed by winter demand.
WHAT IS THE FLU?
Flu – full name influenza – is a viral disease that causes feverish, cold-like symptoms.
Signs that someone has the flu include high temperature, body aches, exhaustion, dry cough, sore throat, headache, loss of appetite and diarrhea.
It is caused by a number of common viruses and tends to circulate every winter, spread through coughs, sneezes and close contact with other people who have contracted it.
The disease usually resolves itself within a week or two in healthy patients.
More vulnerable people such as young children, the elderly or people with asthma, cancer of HIV, may be at risk of more serious complications – people die of flu every year.
For otherwise healthy people, unless they are no longer able to breathe, have sudden chest pain or cough up blood, Flu is not a medical emergency and people should get bed rest or call NHS 111 if they need advice.
The disease is more intense than a cold and causes symptoms such as fever, muscle aches, exhaustion, loss of appetite and headache.
Flu kills around 650,000 people around the world every year.
The findings of the latest study were reported in the medical journal Lancet Digital Health.
People were classified as a flu risk if their weekly average heart rate rose above their normal level, or if they slept more than usual. People get more tired when they get the flu because their bodies use up their energy to fight the virus.
The data was then compared with weekly estimates for flu-like disease rates reported by the US Centers for Disease Control (CDC).
Dr. Radin and her colleagues discovered that by processing the data from Fitbits they could predict outbreaks earlier.
It was the first time that heart rate monitors and sleep data were used to predict flu or an infectious disease in real time.
Scientists added that it might be possible to apply the method to larger areas such as provinces or cities.
Traditional surveillance takes one to three weeks to collect reports from doctors, which limits the ability to be proactive and to fight outbreaks of flu.
All users were notified when they purchased their devices that their data could be used for research.
Dr. Radin and her colleagues have, however, established various limitations for the investigation.
First, the general lack of activity data meant that they could not explain how heart rate and amount of sleep might change due to other factors.
For example, a user’s average heart rate may have been increased or decreased based on how much exercise they received and how physically fit they were.
In addition, weekly resting heart rate averages include days when a person is both sick and non-sick, and this can lead to underestimation of the disease by lowering the weekly averages.
They also warned that devices such as Fitbits are known to be inaccurate, although the researchers acknowledged that they would improve with advancing technology.
And because those who participated in the study were mostly middle-aged adults and probably higher-than-average earners, they had less chance of other problems, making them more likely to have infections such as the flu.
The researchers initially assessed data from 200,000 Fitbit users.
The average user was 43 years old and 60 percent were women.
The sample size was reduced by only using data from those who consistently used their Fitbits during the study period, which ran from March 2016 to March 2018.