Coronavirus cases fell most sharply in the US counties where people stopped going to offices and workplaces, new cellphone data suggests.
The researchers believe patterns they saw in the publicly available cell phone location data could be used to better estimate Covid-19 growth rates and inform decision-making when it comes to shutdowns and “reopenings.”
This study was published in the journal JAMA Internal Medicine.
“This analysis supports the incorporation of anonymized cell phone location data into modeling strategies to predict at-risk counties across the US before outbreaks become too great,” said the study’s senior author Joshua Baker from the University of Pennsylvania in the US.
The research team used location data from cell phones — which were de-identified and made publicly available by Google — to analyze activity across up to 2,740 counties in the US between early January and early May 2020.
This data was broken up into locations where the activity took place, ranging from workplaces to homes, retail stores, grocery stores, parks, and transit stations. Roughly between 22,000 and 84,000 points of data were analyzed for each day in the study period.
The idea was to compare where the cell phone activity took place as a proxy to show where people, themselves, spent their time.
This data was compared between two time periods: the first in January and February, before the Covid-19 outbreak in the US, then mid-February through early May, during the virus’ initial surges and when stay-at-home orders were enacted.
Intuitively, they noted an increase in time spent at home, while visits to the workplace dropped significantly, along with a decline in visits to retail locations (such as stores and restaurants) and transit stations.
They saw that in counties where there was initially a higher density of cases, visits to workplaces, as well as retail locations and transit stations, fell more sharply than counties less affected by Covid-19.
At the same time, in these counties, there was a more prominent spike in activity at homes.
In addition, the researchers saw that the counties where workplace activity fell the most had the lowest rates of new Covid-19 cases in the days that followed.
The research team hopes more work can be done to vet cell phone data to see if they can be specifically used to predict Covid-19 hotspots and guide decision-making.
