Kevin Williams, an associate professor of economics at Yale SOM, was in the middle of a study of consumer retail behavior using real-time cell phone location data when COVID-19 hit. Shelter-in-place orders rolled across the country. Foot traffic at stores froze.
“If you thought the retail apocalypse looked bad a few years ago, that is likely small potatoes compared to right now,” he says.
But as the prospects for one line of research closed down, another avenue opened. Could the same location data be useful in studying COVID-19, he wondered? Partnering with several other researchers, Williams gathered—and continues to gather—real-time information on the movement of millions of individuals across the country as they adapt to the constraints of a pandemic. He hopes that this public repository of information will spur other researchers to investigate patterns and changes in the movement of individuals and how it affects transmission of the disease.
“Typically, in economics, you obtain data, conduct analysis, write a paper and submit it for publication—and the paper is the product,” Williams says. “This work was a bit different: we put the data first. In light of COVID-19, our idea was to create a public good for investigating how devices move across geographies as well as how devices potentially interact at retail establishments.”
By June, the data set contained 53 million devices, each of which had reported location data at least 11 of every 14 days starting in November 2019. The researchers connected each to a demographic profile by making an educated guess at the owner’s home location—based on where the device generally spends the night—and then matching it against census-reported block groups.
The data is organized into two indexes. First, what the researchers refer to as the location exposure index, or LEX. This captures the