New Study: Associations between socio-demographic factors and change in mobility due to COVID-19 restrictions in Ontario, Canada using geographically weighted regression

A team of researchers led by Ben Klar with Jason Gilliland and Jed Long recently published an article entitled: “Associations between socio-demographic factors and change in mobility due to COVID-19 restrictions in Ontario, Canada using geographically weighted regression.”

Transportation research has shown that socio-demographic factors impact people’s mobility patterns. During the COVID-19 pandemic, some of these effects have changed in accordance with changing mobility needs adapting to the pandemic, including restrictions on in-person gatherings, closure of in-person businesses, and working from home.

The researchers investigated two gaps in current knowledge in this area of transportation research: to what extent the associations between socio-demographic factors and mobility metrics have changed, and how these associations vary across geographic space.

They used aggregate deidentified cell tower location data to measure two mobility metrics—movement time and radius of gyration—and socio-demographic data from the 2016 Canadian Census to model these associations across Ontario, Canada in 2020 using a linear model and a geographically weighted regression model.

They found that certain associations between socio-demographics and mobility have changed from what they previously observed before the pandemic, and they can see the variation of these associations across space.

These findings will improve our understanding of how socio-demographic factors affect mobility patterns in different communities and demonstrate the importance of measuring these associations at a more fine-grained level using models that consider spatial variation to best reflect the nature of these associations.

Citation: Ben Klar, Jason Gilliland, and Jed Long. “Associations between socio-demographic factors and change in mobility due to COVID-19 restrictions in Ontario, Canada using geographically weighted regression.” Canadian Geographies 68, 2, 256-275 (2024); https://doi.org/10.1111/cag.12879

Categories: Newsletter

Leave a Reply