Data User Group – Ontario

The same data can be viewed in a variety of ways to support different reflections and discussions. This histogram of the regional distributions of daily reported cases of COVID19 helps you appreciate the volume of cases that the Toronto and Peel Health Units are dealing with…

Whereas this ridgeline plot uses a “free scale”, making the shape of the non-GTA distributions easier to see and consider. Toronto has had a relatively steady increase in the daily reported cases of COVID19. Reported cases for other regions, on the other hand, return more sporadically. This speaks to a variety of considerations including testing capacity, travellers returning home etc.

Updated with Public Health Unit Labels

Original post with PHU’s labelled by Municipal location:

The animated data visualization above was produced in R using the ggplot2 and gganimate packages with open source data from data.ontario.ca.  Data is current up to April 8, 2020.

One of the challenges to understanding the spread of COVID19 data is the availability of data.  Each day, members of the Data User Group have been updating a CSV file on our Github and a shared Google Sheet with information from the Ontario Ministry of Health’s COVID 19 daily updates.  As the capacity for testing has expanded and the number of identified cases has increased, the once detailed tables of data available on the Ministry website has become daily notices: “Information for all cases today are pending.”

Unfortunately, since the Ministry of Health does not provide updates on the reported cases, every record coded as “pending” effectively becomes missing data.  Fortunately, each of the regional Health Units are providing updates on the numbers of cases on their websites.  These regional updates have been useful to validate and cross-reference the tables that Wikipedia has been maintaining (mentioned in the previous post).  This compiled data set is available in the shared Googles Sheet under the tab “Wikipedia”.

Following are a few of the questions we have explored with the data we have compiled (click on the visual to see it in a larger format):

What are the origins of internationally acquired COVID19 cases in Ontario?

Data source: “Wikipedia” tab in the DUG Google Sheet
Tool: QGIS

Where are the confirmed COVID19 cases in Ontario?

Data source: Github csv
Tool: R – Shiny Dashboard, Interactive Map (Greg Rousell)

What does the growth of COVID19 confirmed cases look like in each region?

Data source: Github csv
Tool: R – Shiny Dashboard, Interactive Plots (Greg Rousell)

Data source: “Wikipedia” tab in the DUG Google Sheet
Tool: R

Data Collection Updates

• Records in the Wikipedia tab of the Google Sheet have been cross-referenced with local media reporting to fill in gaps on the formal Wikipedia site.  Links to the media reports are included in the record as an additional reference and validation.
• CDUID codes have been added to the records in the Wikipedia tab of the Google Sheet to make it easier to produce maps in GIS platforms.  These CDUID codes correspond to the 2016 Census Divisions managed by Statistics Canada.  The 2016 Statistics Canada Census Division .shp file (polygons) is available here.
• Some of the data in the Wikipedia tab are reported for aggregated regions.  An .shp file with corresponding merged regions is in development and will be posted shortly.

We are a group of researchers and analysts who are interested in data science and would like to use our expertise to contribute to the understanding of COVID-19 in our communities. 

Looking for data…

One of the challenges we encountered trying to understand the spread of COVID-19 was finding a data source in a format that is easily accessible for analysis.  When we were unable to locate such a file (and finding that the process to scrape data through R was too messy given the formats that the information has been released) we decided to take a manual approach.  Using a few different sources, we have compiled data tables which are easily accessible in R (our favorite) and Python.

…Compiling our own 

March 19, 2020

A COVID19 Googls Sheet for Ontario cases has been created, and is being maintained, with data from an Ontario government website and resources available on two Wikipedia pages. We will continue to update these tables until a more authoritative source of case records is made available, ideally by Public Health Ontario.

Resources: An invitation to explore and dive deeper

As we explore this data we will be sharing visualizations and insights on the Data User Group website. Our hope is that others will find our summaries useful.  We extend an open invitation to others interested in data science to engage in additional analysis and use this data set for your own exploration.  Resources include:

March 19, 2020

• A Github has also been created which will include the R code of our members as well as a .csv file that will be updated regularly.  The Google Sheet will serve as our authoritative data source and the github will serve as our central repository for code.  We invite any who are interested to contribute to the github.
• A Shiny app of the github code has been created to provide interactive explorations of the COVID19 data by regional spread. 

Data Background and Sources

The “Provincial Reporting” tab in the Google Sheet is a compilation of data from this Ontario government website.  This webpage provides a table on new cases of COVID-19 diagnosed in the province.  Following are notes about the data:

• Using the Wayback Machine, the earliest records that could be obtained began at case 32.  
• The first 31 cases were then compiled by parsing the press releases available at the bottom of the page.  
• Currently, case numbers 6, 16, 17 and 18 have not been found in the available press releases.  
• Coding with respect to regional health unit appears to have changed over time.  A new column has been added with recoded health unit labels for consistency. 
• On March 18th the website stopped posting the hospitals the cases are related to.
• The data in the Google Sheet is updated daily from this website, around 10:30 am and 5:30 pm when the data is released.

The “Wikipedia” tab in the Google Sheet is a compilation of data from Wikipedia’s Thematic Google Map.  Included in this map are interactive summaries by region which includes the number of cases, number of patients in local hospitals and buildings that have been impacted.  Following are notes about the data that is published on this page:

• The data in the Google Sheet is updated daily from this website.
• Wikipedia also provides a table  with time-series data for the spread of COVID-19 for each province. The data from this website is available in “Wikipedia National” tab in the Google Sheet and is updated less frequently than the other two tabs.

A posting is now open until February 8, 2019 for a Research Analyst contract position at the Durham District School Board.  The start date for this position is to be determined.  This posting can be viewed on and applied to through applytoeducation.com.

Click here for more information

Summary of the Research Analyst: This position will take a lead role in a project … as part of the Ontario Education Equity Action Plan.

Reports To: Administrative Officer, Accountability and Assessment.

Over the past couple of years the Data User Group and Barrie Region MISA PNC have hosted a “Researcher Coffee Break” where school board employees with research, evaluation and data related roles can connect on a teleconference to discuss current issues, challenges or new approaches to common data sets.

Given the popularity of these periodic teleconferences, the Data User Group is collaborating with the Association of Educational Researchers of Ontario for a day of networking and sharing:

Click here for the flyer which includes a link to the online registration.