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This transcript has been edited for clarity.
welcome to Impact factor, Weekly commentary on new medical research. My name is Dr. F. Perry Wilson from Yale University School of Medicine.
In your pocket, or on your desk, or on your bedside table, there’s a sophisticated GPS-connected tracking device that (probably) has been recording your movement for years. It was Of course you know it as a cell phone, and most of us have the vague sense that it knows more about us than we want. Yes: Big Brother is looking at you.
Is it bad? It certainly stimulates my more libertarian tendencies, but such information is This study Appeared in JAMA Internal MedicineThis shows how mobile location data can predict the new case of COVID-19.
A research team led by Josh Baker (full disclosure: Josh and I live together in UPenn, he’s the furthest one available from the Big Brother) to access county level mobile phone data available nationwide And decided what happened across the country when a home order was placed.
Overall, we can see a dramatic decrease in mobile phone pings in retail stores and workplaces, a slight decrease in grocery stores and parks, and an increase in housing. People were at home.
However, there were some variations from country to country.
For example, counties with high levels of poverty had less diminished activity at work. Probably because the jobs in those areas were not the type of telecommuting. Rural counties also experienced less dramatic behavioral changes after a home order was placed. In counties with high case rates, activity dropped dramatically. People took things seriously.
Obviously, of course, the further away you are from the day of your home order, the less impact it will have. For example, after home ordering, retail activity increased by 0.5% daily.
The change in behavior allowed the team to ask some interesting questions. Will coronaviruses slow down in counties with significantly reduced retail and work activity?
In fact, they did. Taking into account the five-day delay between exposure and symptoms, the team showed that the counties with the lowest level of behavioral changes showed the highest growth rates in cases.
This was true even after adjusting for multiple county-level factors, including the amount of testing performed. Simply put, counties where people did not pay much attention to order at home-for whatever reason-then the growth rate of COVID increased.
Adding cell phone data to other epidemiological information will greatly improve the statistical model for predicting new cases, and cell phone monitoring will be a useful tool to figure out where the next hotspot is It was suggested.
So what do you think about it? Let’s say this is a handy tool. Let’s assume that cell phone surveillance saves lives. Also, keep in mind that this is county-level data, not individual cell phone location tracking. If you have these warnings, I think this is okay. However, there may be a slippery slope between county-level mobile phone data and personal-level mobile phone data, As used by some countries?
To be honest, I don’t think the United States will go there. You can’t even wear a mask. I have no particular fear. In the near future, we will declare victory over ourselves and will love the Big Brother. But 2020 is full of surprises.
F. Perry Wilson, MD and MSCE are Associate Professors of Medicine and Director of Applied Translational Research Program at Yale University. His scientific communication works are located at the Huffington Post, NPR, and Medscape here. He mutters @methodsmanmd Hosting his communication repository www.methodsman.com..
