Who got vaccinated first against SARS-CoV-2?
January 7th, 2021
2 min
This article is brought to you by Datawrapper, a data visualization tool with which you can create charts, maps and tables. Learn more
We don’t know the actual number of COVID–19 cases, deaths & recoveries, just the reported ones. Please read the following visualizations with that in mind.
Covering the coronavirus is a challenge. We’d like to help. Here are more than 20 charts, maps and tables that show the latest coronavirus numbers. You can embed any of them on your own website. Since we know that lots of you use this blog post to actually inform yourselves, you can find visualizations on top. Scroll down to the bottom of this blog post for our thoughts on responsible data visualization in this crisis.
Here’s an index of the content of this article and of all available visualizations. Not all of them are embedded here: Some charts, maps & tables were interesting in March or April 2020, but are not anymore (the doubling time charts, for example). You can still find them on our individual chart pages and in the Datawrapper River; we link to both.
In this GitHub README, you can find our latest changes to the charts, maps, and tables in this blog. (We don’t mention when we fix obvious bugs that appear because the data source changes e.g. how it formats data.)
All these charts, maps, and tables were created with Datawrapper. It’s a simple, free tool used by small blogs and big organizations around the world like the New York Times, SPIEGEL and Süddeutsche. You can try it out here, without signing up.
We’d be happy if you’d use and adapt the charts, maps and tables we show here! To do so, hover over them, then click on the appearing “Edit this chart” in the top right corner. This will open a new tab with the editing process for this visualization. Again, without the need to sign up.
Here you can change many things to your liking. For example:
Once you’re happy with style and wording, go to step 4: Publish, hit “Publish” and embed the visualization in your article, download it as PNG or share it on social media.
Please note: The charts, maps and tables that state the Johns Hopkins University as their source (most of them, sadly) fall under its licensing. You can only use these visualizations for educational and academic research purposes, not for commercial purposes.
As data visualization designers, we have a responsibility towards our audience – an audience that might not be aware that each data visualizations tells a story instead of simply “showing the facts”. Our responsibility is to show the data truthfully. The story we want to tell with our coronavirus visualizations is not about panic, but about calm caution and putting things in perspective. So we considered the following while creating these charts, maps, and tables:
Other people who have thought about how we should visualize the coronavirus are Andy Kirk, Kenneth Field and Evan Peck.
The charts, maps, and tables we offer here don’t work on their own. They need to be put in context for your audience.
The number of *actual* #COVID19 cases contains tremendous uncertainty (estimates in around Seattle alone are 10x larger than the positive tests), but we aren’t visually representing ANY uncertainty because we know the number of *positive tests*.
— EvanMPeck (@EvanMPeck) March 5, 2020
Also, here’s a practical tip: To see the newest numbers in charts, maps, and tables you embed, readers will need to reload your website/article. Consider making that clear in the chart notes, at the end of the article or wherever it fits well.
By now (end of March), there are many data sources available collecting information on both COVID–19 cases and deaths. Here are a few:
The data source for all our charts but some of the ones about Germany is Johns Hopkins University. We access it through the Github repo and via this API by software developer Muhammad Mustadi, which gives us the same numbers as the dashboard, up-to-date.
For the state map of Germany, we use numbers from the Robert Koch Insitute. This source is official, but updated slowly in comparison to e.g. this map by ZEIT Online.
To bring the data in the right format for our Datawrapper visualizations, we used R. You can find the (badly written) R script on Github. We update the charts, maps and tables every 20 minutes.
If you know of other data sources we should consider, please let me know at lisa@datawrapper.de.
As always, let us know if you have any questions, feedback or hints. If they’re any charts you’re missing, also let us know. We’re available at support@datawrapper.de. You can also write directly to me at lisa@datawrapper.de or find me on Twitter (@lisacrost).
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