The power of the a mark, a trail, a sign , was at the root of the invention. Of writing , of maps, of a trailing path recorded. What is in an image? but more than that, what is in a chart? For sure, Charles Snow and Florence Nithingale might come to the mind of many practitioners of Information design in these days. Dataviz has been from the very beginning linked to science and epidemiology, as a way of mapping knowledge, as a way of laying out the ideas and putting them to test.
https://en.wikipedia.org/wiki/Nicolaus_Copernicus#/media/File:Nikolaus_Kopernikus.jpg
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It is, therefore, no surprise that in the current situation many academics and specialists have recurred to data visualizations to make sense of what is happening. Information comes from different places, giving affirmations and contradictions, creating above all, informational noise. In the middle of that, diagrams, chart and maps try to make the most of the data at hand. Tweets announcing the latest dataviz, exploring the evolution of deaths and cases, juggling around dates, projections , dates and places.
-Visuals: screenshots of diverse newspapers
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Antecedents
Data visualization has been used by academics, scientists and people of erudition since a long time ago, either to explain and communicate or for their understanding.
John Snow and the cholera map(describe briefly, show map)
John Snow was a doctor in Victorian London, during the development of the Industrial Revolution. The city was growing and growing as it developed and people came to the city for jobs.
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Detective work
The growth in population and a poor infrastructure create the conditions for the spread of diseases like cholera. Dr Snow, like a detective collecting clues, started to trace the location distribution of the cases in one neighbourhood and concluded that a water pump was at the center of the outbreak.
This, it was assumed, should be because the water in the pump was contaminated. After more studies, it was decided that more hygienic measures were put in place and the cholera epidemic was subdued.
-Visuals: Snow, portrait, London, Snow map, cholera image
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Clean means lives
A statistician who was in charge of the care of injured soldiers during wartime, Florence Nightingale looked forward to implementing more stringent measures of hygiene for the wounded, demonstrating that more casualties were from lack of hygiene than from the war itself. After the measures were implemented, the rate of deaths lowered dramatically. To show this, she developed a diagram to convince the government to implement these measures permanently.
As we can see, the history of data visualization and epidemiology is linked from long ago.
-Visuals: Nightingale portrait, Crimea scene, Nightingale diagram
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Dashboards
In the current times, one of the earlier, if not the earliest, takes on the issue of coronavirus was the John Hopkins University, tracing the path of the pandemic since its first appearance in Wuhan, China. In this case, they elaborate a dashboard map, showing all the related data. This set the path to the approach taking by many media outlets to describe the evolution of the pandemics, doing it through maps.
Visuals: scenes of the website map
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Flatten the curve
Curiously, one of the most distributed and shared graphics about the current situation was made years before. We are talking about the “flatten the curve” graphic, which research has traced back to 2007 and shows how the healthcare system can be impacted when the mitigation measures are not taken, and that has been brought back to the forefront by The Economist dataviz team.
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The devil is in the detail
The emphasis is given to the analysis of the coronavirus The most serious people have taken the issue at hand especially since dataviz is about understanding-and we don't understand very well what is happening.
Use of logarithmic vs linear scale
Plainly speaking, exponential growth scale traces the proportion of the growth, showing us if the pandemic, in this case, is still growing at the same pace (twice, thrice, etc), and to trace this Reuters is using in its reports a logarithmic scale, instead of a linear one.
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By definition, maps are about space. Usually, you can organise the graphics either via a spatial organisation or a time-based organisation. To follow the complexity of this case, a custom approach is needed. The health map is an attempt to do so. Initially, it showed only quantities but in its current form also allows us to discern between new cases and previous cases through a timeline evolution.
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Sometimes maps do not tell the whole story. Some countries or areas are smaller but demographically denser than others and therefore more relevant. How to graphic those details in the analysis?. This is sometimes tricky to show in a map. One approach is logarithmic vs exponential scale that we mentioned earlier.
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The focus was made in the statistics side of the epidemic and its growth,
as the main evidence is mainly the number of cases and the number of cases, which are
the number that is guiding the policies of governments across the world use of numbers (cumulative cases, current cases).
There is a caveat, however, when using this for general information. Some of the maps were using cumulative information, which gives the idea that everything is getting worse and worse in an apocalyptical way. For media of massive reach, this has clear consequences as the public only receive this view and few will care between the difference between these numbers and the number of recovered people, deaths and new cases, all of which are hard to represent in a map at once.
A word of caution has been raised by many specialists about the
The availability of resources is signalled sometimes as a cursed blessing, like when Photoshop appeared and all the graphic design was shadows and 3d-rendered bevels.
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Looking forward
The discussion about the do and don'ts of visualization is full of specifics, details and important considerations which are of common use among the diverse range of specialist in the topic; most of them have been addressed from different angles and continuously and in the middle of the graphic frenzy, there have been improvements that will doubtlessly impact how data viz will be used in the future.
It seems as many say nowadays, that data viz has become mainstream after all.
Visual: “catten the curve”
Other variations of "Flatten the curve"
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Others
While the graphics we have seen are concerned mainly with the statistics and analytic side, others fulfil a communicational and social role, giving indications to the people of what they should do as in this graphic, and in this, they are a clear way to instruct the people on what they should and shouldn’t do.
Visuals: graphic of Ivan C. Palomino for Correo
Graphics of Zarracina about social distancing
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Having seen all this, the good news is that undoubtedly the data viz community, whose practitioners are spread across many disciplines, from science to media, will obtain undoubtedly precious insights about how visualization helped or not to clarify, understand and communicate during this exceptional time. Looking forward to it.
Visuals: Minard, New York Times, other good graphics, “flatten the curve.all one after another
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