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European COVID-19 Forecast Hub [Submission Fork]

This Fork is used to submit weekly updates to the ForecastHub-Eu project. The initial/main repo can be found here.

Bayesian inference of SIR-dynamics

  • Our model is based on the research article available on arXiv and is in press at Science. In addition we published technical notes, answering some common questions: technical notes.

  • We published a python package which we use for our forecasting/modeling approach in this repository: covid19_inference

  • Additional you can find daily updated figures for current numbers in Germany here.

Model

This model simulates SIR-dynamics with a log-normal convolutions of infections to obtain the delayed reported cases. Parameters of the model are sampled with Hamiltonian Monte-Carlo using the PyMC3 Python library. We assume that the infection rate can change every week, with a standard deviation that is also an optimized parameter. When new governmental restrictions are enacted or lifted, we include a small prior to the change of the infection rate.

The scripts to run our model can be found in the MODEL folder.