  In this paper, we estimate epidemiological data of the COVID-19 pandemic in
Hungary using only the daily number of hospitalized patients, and applying
well-known techniques from systems and control theory. We use a previously
published and validated compartmental model for the description of epidemic
spread. Exploiting the fact that an important subsystem of the model is linear,
first we compute the number of latent infected persons in time. Then an
estimate can be given for the number of people in other compartments. From
these data, it is possible to track the time dependent reproduction numbers via
a recursive least squares estimate. The credibility of the obtained results is
discussed using available data from the literature.
