  Data assimilation is used to optimally fit a classical epidemiology model to
the Johns Hopkins data of the Covid-19 pandemic. The optimisation is based on
the confirmed cases and confirmed deaths. This is the only data available with
reasonable accuracy. Infection and recovery rates can be infered from the model
as well as the model parameters. The parameters can be linked with government
actions or events like the end of the holiday season. Based on this numbers
predictions for the future can be made and control targets specified. With
other words: We look for a solution to a given model which fits the given data
in an optimal sense. Having that solution, we have all parameters.
