During COVID closure, Western researchers use telephone data to track Ontarian movements

During COVID closure, Western researchers use telephone data to track Ontarian movements

“We found that there really wasn’t evidence that supported that people —more than expected or more than usual — moved from those higher lockdown regions to non-lockdown regions,” said Jed Long, an assistant professor with the department of Geography and Environment at Western University and lead author of the study. The study used anonymized cell phone data provided by Telus Mobility to determine the effectiveness of lockdowns, focusing on the weeks around July 17th and November 23rd of 2020, when large areas of the province had various levels of travel restrictions.

He said that’s likely due to lower-income communities having a higher percentage of frontline workers. “That finding has been essentially found throughout the globe,” said Long. “Basically everywhere where they’ve studied lockdowns and and mobility patterns, they’ve seen that … people have restricted their mobility more if they have more money.” The study, published in the journal Computers, Environment and Urban Systems, compared mobility data from February 2020, when data collection began, and continued throughout the year.

Story Highlights

  • A pair of studies from London’s Western University shed insight on how Ontarians travelled throughout the province during last year’s lockdown restrictions and who was able to comfortably stay at home. The first, just published in the journal Health & Place alongside academics from Athabasca University, found that Ontarians in high-restriction areas like Toronto and Peel Region mostly stayed put during the lockdown.

  • “One of the things that was floated around in the media was that people might leave those areas to go to other areas in the province to access services,” said Long. Western researchers did find one area where Ontarians’ mobility correlated directly with their living situation — income. A second study using mobile data looked at associations between mobility and socioeconomic indicators. “Mobility didn’t change as much if you’re a person with low income, he said. “But if you’re an upper-income person, all of a sudden your mobility is greatly reduced.”