The coronavirus death toll

Simon Jockers

Hi, this is Simon, I am a software engineer at Datawrapper. For this week’s edition of the weekly chart, we’ll take a look at a tough topic: Excess mortality in the coronavirus pandemic.

The first confirmed death in the coronavirus outbreak was in Wuhan on January 9th 2020. Since then, at least 350.000 people have died from COVID-19, according to official WHO figures. New York City has been one of the epicenters of the pandemic with thousands of deaths over just a couple of weeks:

The above chart shows the devastating number of deaths that New York City has been experiencing each week compared to the weekly average of the past years. The difference between both numbers is called excess mortality. It includes deaths from COVID-19 but also deaths due to other causes, like the overwhelmed health system.

Excess mortality is shockingly high in the cities that are hit hardest by COVID-19, such as New York City. If we look at whole countries, the mortality rates of many less affected areas get counted in. Still, the effect of the pandemic is visible:

About the data

Over the past weeks, there have been several excellent reports on the death toll of the pandemic by teams at the New York Times, The Economist, and the Financial Times. Reading those got me interested in the topic so I had a look at different data sources and did some number crunching myself.

To create the New York City chart, I used data that a team at the New York Times collected and processed for their own reporting and subsequently published in a Git repository. The data set includes the numbers for New York City and a range of countries – but not for the ones I was interested in, such as Spain and the United States. I did some research and ended up creating the per country charts based on data from the Human Mortality Database, a joint project by academic research teams at the University of California in Berkeley and the Max Planck Institute for Demographic Research.

I downloaded the data set on Short-term Mortality Fluctuations (STMF) from the Human Mortality Database and used R to extract the data, to calculate the average mortality for each week and country, and to prepare the data for charting in Datawrapper. I then created the individual graphics in Datawrapper. If you want to check out how that’s done, hover over the charts above and click on Edit this chart to get right into the line chart tool.

If you are interested in working with excess mortality data yourself, have a look at the following resources:

• My collection of basic R scripts for processing excess mortality data
• An intro to excess mortality from COVID-19 by Our World in Data
• The Human Mortality Database by the MPIDR and UC Berkley
• Excess Deaths During the Coronavirus Pandemic by the New York Times
• EuroMOMO, the European mortality monitoring project

That’s it from me for this week. As always, do let me know if you have feedback, suggestions or questions. I am looking forward to hearing from you at simon@datawrapper.de, Mastodon, or Twitter. We’ll see you next week!

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Simon Jockers

(he/him, @sjockers) was a software engineer at Datawrapper between 2018 and 2022, where he contributed to the chart editor and to chart types. Outside of Datawrapper, he helps organizing the Berlin Hacks/Hackers meetup and works on way too many side projects.

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