Covid19 Hackathon: Programming new applications from data

Since the beginning of March, the Statistical Office of the Canton of Zurich and its specialist and coordination unit OGD (Open Government Data) have been collecting all data relating to the coronavirus, thus creating an openly accessible data basis. Useful applications were programmed from the data at the “Monitoring COVID-19 Effects Hackathon”. Public statistics specialises in providing high-quality, broad-based and very reliable indicators. In this way, it enables well-founded political decisions. In the current situation, however, the classical indicator systems of public statistics are reaching their limits. The situation is very dynamic and changes daily or even hourly. It is important that those working in the health system and in primary care are not bothered by surveys. There is a need for quasi real-time data from the health system on case numbers and hospital utilisation, on the economy and society. The cooperation between public statistics and the open data community is a great opportunity, especially in times of crisis, to provide reliable data as quickly as possible. In order to avoid flying blind, politics, administration and also the economy are dependent on timely and high-quality information on the current situation. On 5 March, the first data set on COVID-19 case numbers was published by the Health Department of the Canton of Zurich on, the federal government’s open data platform. The great response from the Open Data community has shown us how strong the need for these data is among the public and in research. That is why the Statistical Office called for the COVID-19 Effects Monitoring Hackathon. Thanks to the support of Oleg Lavrovsky from, it took just two hours from idea to implementation. Already on 17 March, we called for participation on Twitter. Within a very short time and without any further advertising, around 50 participants were working on obtaining the urgently needed data basis for dealing with the crisis and analysing the first indicators of the effects. Of course, the hackathon was conducted completely virtually, including social distancing.

A selection of the projects

Individual tasks (challenges) were advertised on the hackathon website, and participants could then sign up for one or more challenges.

  • Cantonal COVID-19 case numbers

Our goal is to create a common official OGD dataset of COVID-19 cases of the Swiss authorities. The data is uniformly structured and regularly updated and available as machine-readable Open Data resources. We want to achieve this goal together with the Open Data community. At the beginning of the hackathon, case data on 20 cantons and the Principality of Liechtenstein was missing. In the meantime, data on all cantons can be published at regular intervals.

  • Evaluation of control measures

In order to be able to compare the effects of the measures, an overview of the measures taken per canton is needed. This Challenge is intended to collect this information and make it available to a broad public.

  • Data on hospital infrastructure

In order to provide models with meaningful parameters, we need detailed data on hospital infrastructure and bed capacities and utilisation per hospital. This Challenge aims to combine data on the capacities of the Swiss healthcare system from different sources and to create an open and free dataset.

  • Impact on air quality

Do we see effects of the Covid19 epidemic in the pollution?

  • Visualisation of case numbers in the cantons

We try to discuss the various illustrations of the collected case numbers of the cantons here and improve them together. If you have ideas for a visualisation of this, you can build on this resource. Furthermore, we would like to have a discussion about responsible data visualisation in this project.


All information about the hackathon and a short summary of the presentations can be found here.

Another hackathon starts today: #CodevsCovid.

Creative Commons Licence

AUTHOR: Matthias Mazenauer

Matthias Mazenauer is deputy head of the Statistical Office of the Canton of Zurich. He also manages the office's datashop.

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