Visualising NSW Health data on Covid-19 Testing
Once again, NSW Health has led the way in providing transparency around the data they have on the coronavirus/Covid-19. This time, they’ve released data showcasing the areas and age groups that are getting tested for Covid-19 and what those results are. You can see this data here: https://data.nsw.gov.au/nsw-covid-19-data
As a reminder, we were already getting confirmed cases data released in this format by NSW Health and we used it to publish the Prosperity tracker that you can access here: https://medium.com/prosperity-advisers-dna/nsw-covid-19-dashboard-6ac44eec3811
Instead of putting it all into the one app, I thought it would be best to showcase another design style so that viewers can see the other ways that data can be presented.
The App
You can access the app here: LINK
Caveats
There are a couple of limitations to this app with the first one being that we had to truncate (i.e. cut) some of the data as it did not have either age group classifications or area details. This means that the data shown here (as at 4th May) is not 240k tests conducted, it is actually more. However, the data shown is where tests have occurred so its important to stick with where there is available data. The same thing happens with age groups. The missing amount is only a few percent of the total so it does not make a huge difference.
Features
There are 6 sections to this app covering a couple of different areas. The data is mostly all available in the Excel files provided by NSW Health but making these interactive and filterable makes it easier to explore.
On the left hand side we have the navigation menus and above some pages are some sub-menus which you’ll see later on.
In each section the user can see some total figures at the top of the page pertaining to # of total tests, # of positive results and the percentage rate of positive tests.
There are filters at the top of each page allowing you to change dates and also choose the area by LGA or Suburb (ie Locality). There is also the ability to filter between positive results and results that tested negative.
If you want to expand any chart you can do that by hovering over it and click the expand button so that the chart takes up the full screen.
The charts are interactive and you can make selections either from the filters or clicking on the charts themselves. You can make multiple selections on charts by holding down the CTRL button as you make your selections too.
Pages
# of Tests
This is the landing page for the app. It shows the total numbers of people being tested historically as well as per LGA or Suburb. If you click on an LGA like Blacktown, you can see what postcodes relate to it as well as what it’s historical testing looked like.
% Positive
This page looks at the percentage rate of positive tests for LGA’s and their suburbs. We can see the LGA of Federation has the highest percentage of positive tests at 10% (meaning 10% of its tests turned out positive) but we can see that they’ve only had 80 tests, which is small compared to many other regions.
Maps
This page shows the maps of testing hotspots across NSW. You can use the filters to change how this looks such as looking at what the testing looked like at the start of March.
Age Group
This table, as provided by NSW Health, only has dates of tests and the age cohorts so it is not possible to connect it to the area data we’ve seen so far. As such, this page only has 1 filter at the top of the page.
We can click on the bars or use the filters to see that 20–29 year old persons were being tested mostly in March but that has slowed down.
And that those in the 70+ age bracket have seen their testing ramp up later in April.
Demographics vs # Tests
This section is where we have sub-menus. Once you click on this section you can see 4 sub-menu options looking at Population, Population Density, 15–64 y/o and >65 y/o. These groups are the same as the demographic data we looked at in the NSW Confirmed cases tracking app mentioned at the start of this article.
This entire section looks at those demographic datasets and compares them to the # of Covid-19 tests per the NSW Health data. In the following image, we are looking at Population Density and # of Tests. The positive slope of the trend line indicates that more population dense suburbs had more tests
Demographics vs % Positive
This final section looks at the same scatter charts before but this time instead of looking at # of Tests performed, it looks at the % Positive rate per LGA area.
In the screen below we’re looking at % Positive rate plotted against the suburbs with a higher percentage of senior (> 65 y/o) residents.
Get in touch
For more information about this app or other things data analytics related, feel free to get in touch with me below.
Mark Monfort (Head of Data Analytics and Technology, Prosperity Advisers)
- Phone: 02 8262 8700
- Email: mmonfort@prosperity.com.au
