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COVID-19 Inference and Forecast

How effective are interventions?

Our paper about estimating the effects of governmental interventions on the spread of COVID-19 is now out in Science!


Over the past months, my colleagues and I have worked on modeling the COVID-19 spread in Germany. Our approach uses Bayesian inference and Markov-Chain Monte-Carlo sampling on an SIR-model to find epidemiological parameters. It allows us to identify change points in the spreading rate (that is, when and how much the spreading rate changes). Check the links below for all the details!

[Science] [ArXiv] [GitHub]

I want to take the opportunity to thank everyone involved for this amazing collaboration. This has been, and still is, a truly great team effort. I feel that we have made a valuable contribution, and for me personally, the project made quarantine and working from home much more enjoyable! Thanks guys!