Data visualization in a time of pandemic - #6: Viral scrollytelling

Title: data visualization in a time of pandemic

Chapter 6: Viral scrollytelling

In this final chapter, we’ll dive deeper into some of the insightful stories which have been published about the novel coronavirus and the COVID-19 pandemic. Rather than looking at single charts, we’ll highlight some long-form stories about the origin of the virus, how it works, and how it spread.

Two concepts should be explained beforehand: visual storytelling, and scrollytelling. Lorenzo Amabili explains both of them very well in his Nightingale article ‘From Storytelling To Scrollytelling: A Short Introduction and Beyond‘ (unfortunately a premium article):

  • Visual storytelling, also called narrative visualisation, consists of creating a logical sequence of related (data-driven) visualisations, or visual elements, needed to convey a message to an audience in an engaging and effective way.

In other words, different visuals are strung together to form a logical story, which will keep readers more engaged and increase their understanding. It also allows you to discuss more complex topics by breaking them down into multiple easily understood visuals. These visuals will often be data-driven, but they can also be illustrations, videos, maps,… the possibilities are virtually endless!

storytelling illustration

  • Scrollytelling is visual storytelling for the web: a powerful technique based on a simple concept: new content and visuals appear or change through transitions as users scroll down or up the web page.

This way of presenting information keeps the reader actively engaged with the content and the story. Furthermore, people can easily control the pace by scrolling up and down, back and forth through the story if they choose to re-read difficult sections or skip certain less interesting parts.

I must admit, I absolutely LOVE ❤ scrollytelling, and particularly well-executed examples are appearing more and more regularly in journalism. These advances are fueled by more innovative newsrooms such as the New York Times or the Washington Post, but quickly spreading throughout the world. For example, in Belgium, De Tijd regularly brings engaging scrollytelling stories by the team of Thomas Roelens and, before that, Maarten Lambrechts.

The remainder of this text is dedicated to some remarkable and marvelous examples of visual storytelling and scrollytelling about the coronavirus pandemic. This is absolutely not intended to be an exhaustive list, but rather a collection of interesting examples I encountered during my background research for these blog posts.

Anatomy of a killer

In March, The Economist published ‘Understanding SARS-CoV-2 and the drugs that might lessen its power‘, an in-depth story about the science behind the virus: how is SARS-CoV-2 built, how does it work and replicate itself, what does its genetic sequence look like, and which drugs might have a serious shot at eliminating it. A pretty hardcore scientific explanation, but made easily digestible thanks to some very clear and beautiful illustrations, such as this one by infographer Manuel Bortoletti:

coronavirus illustration

Flattening the curve, revisited

Several scrollytelling articles have been created to explain the reasoning behind the epidemiological curve, how we can flatten it, and differences between different countries’ strategies to do so.

how epidemics end simulation

Detail from ‘How epidemics like covid-19 end (and how to end them faster)’ (Washington Post)

How the virus got out

How the Virus Got Out‘ by the New York Times uses mesmerizing animations and crystal-clear maps to show how the virus spread from Wuhan, through long-distance train and air travel, to other parts of China and other countries throughout the world. They end with Donald Trump’s quote ‘The virus will not have a chance against us’ on March 11, placed next to a visual showing how by then, the virus already had a secure foothold in the US, with just over 1000 cases.

how the coronavirus got out

Detail from ‘How the Virus Got Out’ (New York Times)

This detailed look at how the virus spreads is taken one step further by Reuters Graphics in ‘The Korean Clusters‘. Thanks to insanely accurate contact tracing data being gathered in South Korea, the authorities were able to identify each individual case and how they infected each other. During the first four weeks, the disease was relatively contained, but then ‘patient 31’ emerged, who had at least 1160 traced contacts and went to crowded places such as churches and a hotel buffet while being infected. This is by far one of the most captivating visual stories I have encountered over the past few months!

coronavirus south korea patient 31

Detail from ‘The Korean Clusters’ (Reuters Graphics), an amazing piece of visual storytelling.

How bad will it get?

It is worth mentioning two stories detailing how the virus can spread, in particular in public transport or between people passing by each other outside:

  • South China Morning Post describes a situation where a sick traveler on a four-hour bus journey (feeling sick but not wearing a mask) infected 9 other passengers – complete with detailed seating plans of the bus in question.
  • The New York Times describes 6 key factors determining how bad the epidemic will get, including how contagious and deadly the virus is, and how long it will take before a treatment or vaccine is developed. They also indicate how far the virus can typically travel in a public transport environment.

coronavirus on public transport

Detail from ‘How Bad Will the Coronavirus Outbreak Get?’ (New York Times)

Remembering lives lost

In the end, it’s all about people. In his article ‘The Workers Who Face the Greatest Coronavirus Risk‘ for the New York Times, Lazaro Gamio uses scrollytelling to guide readers through a stunning scatterplot, showing which professions are most at risk during the pandemic, either because they come in close contact with others (such as hairdressers), or because they have a high exposure to diseases (such as garbage collectors or healthcare workers). The article ends with an interactive version of the graph, enabling readers to explore the data themselves.

coronavirus risk professions

Detail from ‘The Workers Who Face the Greatest Coronavirus Risk’ (New York Times). Did I already mention that I scrollytelling stories like this?

Let’s end this exploration into pandemic data visualization with one of the most heartbreaking visual stories, published by the New York Times on May 24, 2020. ‘An Incalculable Loss‘ visually shows the 100 000 lives lost to COVID-19 in the US up to that point. 100 000 figures, many of them with additional information making it all the more real. “Marion Krueger, 85, Kirkland, Washington. Great-grandmother with an easy laugh.” Or “Torrin Jamal Howard, 26, Waterbury, Connecticut. Gentle giant, athlete and musician.”

coronavirus 100000 deaths

Detail from ‘An Incalculable Loss’ (New York Times)

100 000 times.

Cherish the people you love and the present moment, as scary as it is. It is all we have for certain.
Daily Stoic

Stay safe, everyone. ❤

This is a multi-chapter blog post!

Continue reading:

For all your comments, suggestions, errors, links and additional information, you can contact me at or via Twitter at @koen_vde.

Disclaimer: I am not a medical doctor or a virologist. I am a physicist running my own business (Baryon) focused on information design.

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