Modeling and visualization of the COVID-19 pandemic in Ontario

Follow:

  • RSS
  • Cite
Image
""
Submitter Name
Kaitlyn Hobbs, Sofia Bahmutsky, Ngan Lyle, Shreeram Murali
Summary

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).

Impact

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

Testimonial(s)

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

Votes: 86

Add new comment

Rules of Engagement

We look forward to hearing from you. Your ideas and feedback are central to the development of both the Open Government portal and the Government of Canada’s approach to Open Government.

While comments are moderated, the portal will not censor any comments except in a few specific cases, listed below. Accounts acting contrary to these rules may be temporarily or permanently disabled.

Comments and Interaction

Our team will read comments and participate in discussions when appropriate. Your comments and contributions must be relevant and respectful.

Our team will not engage in partisan or political issues or respond to questions that violate these Terms and Conditions.

Our team reserves the right to remove comments and contributions, and to block users based on the following criteria:

The comments or contributions:

  • include personal, protected or classified information of the Government of Canada or infringes upon intellectual property or proprietary rights
  • are contrary to the principles of the Canadian Charter of Rights and Freedoms, Constitution Act, 1982
  • are racist, hateful, sexist, homophobic or defamatory, or contain or refer to any obscenity or pornography
  • are threatening, violent, intimidating or harassing
  • are contrary to any federal, provincial or territorial laws of Canada
  • constitute impersonation, advertising or spam
  • encourage or incite any criminal activity
  • are written in a language other than English or French
  • otherwise violate this notice

Our team cannot commit to replying to every message or comment, but we look forward to continuing the conversation whenever possible. Please note that responses will be provided in the same language that was used in the original comment.

Our team will reply to comments in the official language in which they are posted. If we determine the response is a question of general public interest, we will respond in both official languages.