Researchers tracked data from millions of mobile phone users in major US metropolitan areas and compared the data to neighborhood demographic information
Credit: University of Arkansas
FAYETTEVILLE, Ark. – Fine-grained location data gleaned from mobile phones shows that people living in less affluent neighborhoods spent less time at home during the early lockdown and first several months of the coronavirus pandemic.
Researchers tracked data from millions of mobile phone users in the largest U.S. metropolitan areas. Their findings contribute to a growing body of research suggesting that low-wage earners — a vulnerable group already at greater risk for contracting COVID-19 — could not afford to comply with stay-at-home orders or worked in professions that prohibited working from home.
“Our study reveals the luxury nature of stay-at-home orders, which lower income groups cannot afford to comply with,” said Xiao Huang, assistant professor of geosciences in the Fulbright College or Arts and Sciences. “This disparity exacerbates long-standing social inequality issues present in the United States, potentially causing unequal exposure to a virus that disproportionately affects vulnerable populations.”
By mid-March of 2020, weeks after the first coronavirus case in the U.S., most states ordered some form of lockdown. Officials advised people to stay home to slow the spread of the virus. Non-essential businesses closed, and millions of people were asked to work from home.
Huang and his colleagues wanted to understand the extent of compliance with these orders. They analyzed anonymous tracking data from 45 million mobile-phone users and calculated how much time residents in the cities of New York, Los Angeles, Chicago, Dallas, Houston, Washington, Miami, Philadelphia, Atlanta, Phoenix, Boston and San Francisco spent at home between Jan. 1 and Aug. 31 of 2020.
The researchers then compared these data with demographic information about neighborhoods within these major cities. The demographic information was obtained from the American Community Survey, a demographics survey program conducted by the U.S. Census Bureau.
People living in areas with a higher percentage of wealth and higher average household income level spent more time at home during the stay-at-home orders than people living in poor communities, the researchers found. This finding was valid for all cities.
The study also demonstrated a correlation between education and stay-at-home compliance. People who lived in neighborhoods with a high percentage of college degrees spent more time at home.
Huang said the findings could lead to a reassessment of the long-term impact of COVID-19 on geographically and socially disadvantaged groups.
“The disparity in responses to stay-at-home orders reflects long-standing social inequity issues in the United States, potentially causing unequal exposure to COVID-19 that disproportionately affects vulnerable populations,” said Huang.
For this project, Huang collaborated with with Junyu Lu at Arizona State University, Song Gao at University of Wisconsin, Sicheng Wang at University of South Carolina, Zhewei Liu at Hong Kong Polytechnic University and Hanxue Wei at Cornell University.
The researchers’ findings were published in the journal Annals of the American Association of Geographers.