Do you fully understand the Coronavirus graphic information received through the media? Can you make a critical reading of graphics or numerical tables to understand their accuracy? IDSC Visualization Director Dr. Alberto Cairo was interviewed by Guillermo Arduino of CNN en Español, and spoke with CBC News Canada on how to read graphics and distinguish the truth from visual misrepresentations of data on the Coronavirus.
“Coronavirus: Lo que no dicen los gráficas” by Guillermo Arduino of CNN en Español
“The flurry of daily pandemic data can be overwhelming. Here’s how to make sense of it.” by Roberto Rocha CBC News
Dr. Cairo is also quoted in a CBC News story (CBC News is Canada’s publicly owned news and information service) story, entitled: “The flurry of daily pandemic data can be overwhelming. Here’s how to make sense of it.” Roberto Rocha looks at how statistics and charts can be enlightening—provided you know the key context of what they show.
The article takes, for example, the COVID-19 ‘dashboard’ from the Johns Hopkins Center for Systems Science and Engineering (which was one of the first to compile and publish global data on new cases) . . .
and illustrates how the use of the same size circles for New York (the city) and Italy (the whole country) is misleading at a glance. Dr. Cairo (author of the book How Charts Lie: Getting Smarter about Visual Information) told CBC News “it would be more accurate to show the U.S. as a big bubble on a global scale ‘that splits apart by city or county when you zoom into the U.S.'”
As Dr. Cairo illustrates for CBC News, “Even the size of bubbles depicting the severity of the spread can be misleading. For example, New York City and Italy have circles of similar sizes, even though Italy has nearly four times the number of confirmed cases as New York.”
The CBC News article sheds light on Daily Confirmed New Case Numbers (which has a time delay) versus Actual New Case Numbers (which can be far higher), through in-depth analysis commentary on a video made by nonprofit education site Khan Academy. The article also looks at the problematic issues that there is no universal definition of a confirmed case or of recovery, that exponential growth is tricky to understand, and other terms like: cumulative cases, death counts, testing rates, and fatality rates.