  A major difficulty in the analysis of propagation of the coronavirus is that
many infected individuals show no symptoms of Covid-19. This implies a lack of
information on the total counts of infected individuals and of recovered and
immunized individuals. In this paper, we consider parametric time varying
Markov processes of Coronavirus propagation and show how to estimate the model
parameters and approximate the unobserved counts from daily numbers of infected
and detected individuals and total daily death counts. This model-based
approach is illustrated in an application to French data.
