SZ Vaccination Bot: When is your turn?

Country/area: Germany

Organisation: Süddeutsche Zeitung

Organisation size: Big

Publication date: 22/01/2021

Credit: Christian Endt, Verena Gehrig, Simon Groß, Christian Helten, Stefan Kloiber, Christina Kunkel, Sören Müller-Hansen, Lea Weinmann, also involved were Benedict Witzenberger, Moritz Zajonz and Malte Hornbergs


Süddeutsche Zeitung’s award-winning Data Team was established in 2018 to focus on data-driven reporting across all topics, with close links to the Investigations team (known for the Panama Papers, among other stories). Although it is a standalone unit of the newsroom, the team always works very closely with specialist editors from the other departments, graphic designers and developers, combining their expertise and skills with their own to achieve the best result for readers. As the team sees it, data journalism is first and foremost journalism – its goal is to tell stories, explain complex issues, expose injustice and corruption. The team is committed to constantly learning, experimenting with new tools, sources and storytelling formats, and providing the best possible experience for Süddeutsche Zeitung readers – online and in print. Exchanging ideas, sharing knowledge and learning from each other are important pillars of the philosophy. Towards their readers, they try to be as transparent as possible – publishing detailed descriptions of their methodology, source code and raw data wherever possible. 

Project description:

As soon as the first vaccines against the coronavirus were authorized in Germany, people’s most pressing question was when they could expect to be vaccinated. To prioritize groups particularly at risk from the virus, the government introduced vaccination prioritization, known as the vaccination queue. This order of population groups, available vaccine doses and capacity determined how quickly people could get their shot. With SZ’s vaccination bot, readers could find out when it was their turn in just a few steps.

Impact reached:

The project was very well received, both by loyal SZ readers and newcomers, as it was the first tool to provide personalized answers to the question “When is my turn?”. The article was shared a lot on social media and also attracted attention within the industry. 

Techniques/technologies used:

Two factors go into predicting a vaccination schedule: The sizes of the various prioritization groups and the vaccination rate. Both factors can only be approximated or estimated. For this purpose, SZ consulted all information and current data on vaccination progress, vaccination readiness, vaccination capacities, planned vaccination dose deliveries and the number of residents per prioritization group in the federal states and asked state and municipal offices for further information. Current data was automatically scraped from state and local government offices. The bot is based on draw.io and R.

What was the hardest part of this project?

As with many other Corona topics, vaccination and prioritization data and regulations were subject to many changes. Data sources and formats changed, measures and vaccines were added, and vaccination groups were adjusted. The team had to respond to these changes on short notice to continue to provide the service. The project gave everyone their own personal glimmer of hope: it showed current progress with vaccinations in Germany and when it would be your turn. It explained vaccination prioritization and helped readers find themselves in the vaccination queue. The personal vaccination date was a proxy for vaccination progress in general. As more vaccines were added and vaccination capacity increased, for example by supplying primary care practices, the date also moved closer. Supply shortages, in turn, pushed the date back again.The Vaccination Bot thus told readers how well the vaccination campaign was going, using the readers themselves as an example.

What can others learn from this project?

This project is a good example of how to communicate a topic by breaking it down for the reader to see how it affects them personally. It’s also an example of how a service piece that answers an urgent information need can be a proxy to rehash a larger context, in this case, vaccine queue setup and vaccination progress in general. And it shows how interactive questionnaires can be used in a meaningful way to inform.

Project links: