Researcher
Professor Di Cook has been monitoring the COVID-19 data with her own web app. A link is provided to the source code, so others can download, run, modify, and learn how different plots and data wrangling are done.
The data is automatically extracted from different public sources, and plots are created in order to understand the progression and effect of the pandemic across the globe, and at least initially in Australia. This has been useful for several of our classes, where developing web apps for communicating data is being taught. There are various conscious choices in the design: (1) focus on local, because we needed to get a better idea of the trend of incidence, testing and mortality in Australia in the early weeks when other web sites had little about us; (2) calibrate counts and tests by population so we could compare the response by state; (3) not process the data too much, which doesn't address the differences reporting between countries but also doesn't impose a belief; (4) focus on "not mortality rates" because that's more encouraging; (5) compare incidence and recovery rates for Australia with China, to get a sense for when we would expect the end of the crisis here; (6) pull data such as pedestrian traffic in Melbourne and compare with last year to see if people are heeding the government instructions. She has also pulled CO2 data to see if there is a climate benefit, but it's too early to tell. Data used in the app comes primarily from Johns Hopkins, with Australian data extracted from the rapid compilation made by the Monash FIT-led "The real-time COVID-19 status in Australia".
