Predicting the Common Cold
Why heart rate variability may be key to cutting down on sick days
If you’re an adult, chances are good that you’ll come down with a cold or the flu at least once this year. The two most common viral respiratory infections can take you out for several days at a time. In fact, by the time you turn 75, you will have had about 200 colds and spent a total of 2 years coughing and sneezing.
A financial downer
Aside from being an annoying waste of everybody’s time, coming down with a cold or flu is also expensive. Consider the following:
- Nearly 111 million workdays are lost because of the flu each year, costing employers $7 billion per year in sick days and lost productivity.
- In the US, each cold experienced by a working adult caused an average of 8.7 lost work hours. The economic cost of lost productivity due to the common cold is estimated to be about $25 billion
- Cold and flu viruses account for about 75 to 100 million physician visits every year which equals about $7.7 Billion dollars.
- In 2011, Americans spent $4.2 billion on nonprescription cough and cold remedies
In spite of these huge losses, scientists have yet to figure out a way to treat the common cold or flu. All of the available pills, syrups and cold rubs simply alleviate the symptoms — they doesn’t make the cold itself go away.
Once you start feeling the symptoms, the only thing you can do is wait it out.
But what if there was a way to predict the risk of catching the flu or cold before we feel any symptoms, leaving us with plenty of time to take preventative measures?
We think it’s possible, and the answer may lie in a method called heart rate variability (HRV).
HRV: a brief introduction
HRV is a health assessment method based on analyzing the variation in time intervals between heartbeats. It is a non-invasive, objective way to figure out what’s happening with your body in real time. Originally developed and used in space medicine to assess astronaut health, it is now widely used in fields like professional sports.
At Welltory, we use HRV algorithms to estimate people’s stress & energy levels.
Our app uses a smartphone camera to take the measurement and matches it with data about the user’s lifestyle (sleep duration, number of steps, the weather, etc.). Then, the app generates recommendations in order to help people cut down on stress and start feeling better.
HRV & the common cold
After collecting measurements for a little over a year, we noticed that specific changes tend to occur in people’s HRV indicators before they get sick. Now, we’re on a mission to develop a formula for calculating the risk of coming down with a cold or flu.
Our extensive database of 250,000+ HRV measurements supplemented with data about people’s lifestyles puts us in a unique position. We have access to one of the largest HRV databases in the world, along with a team of talented analysts to help us crunch the numbers and come up with a formula.
Plan of action
- Select 300 users who meet our criteria. Scan our database of 40,000+ users who have had the flu or the common cold while using our app.
- Interview users in order to separate them into subgroups. Factors like age and level of physical fitness can significantly influence default HRV measurements.
- Within each group, analyze how HRV indicators changed during the onset and throughout the illness. These indicators will also need to be supplemented with lifestyle data.
- Analyze the data in order to come up with reverse trends for every person and generate a formula that predicts the risk of catching a cold.
Why it matters
If we can figure out a way to calculate a person’s individual risk of catching a cold, we will surely be one step closer to figuring out ways to prevent them.
Some studies suggest that preventing the cold and flu is about changing our lifestyle habits. A 2010 dissertation on pandemic influenza on university campuses, for example, shows that increased exposure to stress is significantly associated with increased rates of influenza-like illness.
Cutting down on the number of common colds via preventative measures can keep millions of people from wasting a few weeks a year sneezing and coughing in bed. Moreover, it can help reduce healthcare costs and save companies all over the world millions of dollars in sick leave losses.
We’re excited to start our experiment, but first we need to raise $3,000 to cover the costs of interviews and pay our data scientists. We set up a crowdfund on Experiment.com, which gives people who fund scientific discoveries access to data, progress, and results directly from the team. There is no minimal pledge amount, so every bit helps us reach our goal. Click here to learn more and support us!