Modeling and visualization of the COVID-19 pandemic in Ontario


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Submitter Name
Kaitlyn Hobbs, Sofia Bahmutsky, Ngan Lyle, Shreeram Murali

During COVID-19 pandemic, nursing homes and retirement facilities were being particularly hit.

To provide insight on the spread of COVID-19 among these high-risk areas, Statistics Canada worked with students from the University of British Columbia’s Master of Data Science Okanagan program. Together, they analyzed data on Ontario’s long-term care homes in addition to assessing health factors and proximity to amenities across different Public Health Units (PHUs).

To model the spread of COVID-19 in public health units, the team used Statistics Canada’s Health Characteristics dataset, the 2016 Census of Population data products, and the Proximity Measures Database.

Through their analysis, the team helped to uncover that Ontario PHUs that were closer to public amenities such as healthcare, employment, and transit, had higher proportions of COVID-19 infections. The team also discovered that the factors that increased the risk of a COVID-19 outbreak in a long-term care facility were the number of beds in the facility, and the number of inspections initiated as result of a complaint against the home.

This research represents early work in determining the risk factors associated with COVID-19 in PHUs of Ontario and long-term care homes and  offer a deeper look into situations at Ontario’s long-term care homes and PHUs that may have influenced COVID-19 outbreaks during the first wave of the pandemic (up to June 22, 2020).


This project helps provide greater insight into the risk factors associated with an increased vulnerability to COVID-19.


Statistics Canada’s Open Database of Health Facilities was the backbone to our research project. It offered a validation method for the list of long-term homes we collected and provided necessary variables for our analyses. After the capstone project finished, I was able to continue my research on LTCs in British Columbia and Ontario with the University of Toronto. A collection of datasets is also in development, which will provide access to the data used in this project and help encourage collaborative research efforts and open data initiatives.

- Kaitlyn Hobbs, Statistics Canada

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