  The novel coronavirus disease (COVID-19) has spread rapidly across the world
in a short period of time and with a heterogeneous pattern. Understanding the
underlying temporal and spatial dynamics in the spread of COVID-19 can result
in informed and timely public health policies. In this paper, we use a
spatio-temporal stochastic model to explain the temporal and spatial variations
in the daily number of new confirmed cases in Spain, Italy and Germany from
late February to mid September 2020. Using a hierarchical Bayesian framework,
we found that the temporal trend of the epidemic in the three countries rapidly
reached their peaks and slowly started to decline at the beginning of April and
then increased and reached their second maximum in August. However decline and
increase of the temporal trend seems to be sharper in Spain and smoother in
Germany. The spatial heterogeneity of the relative risk of COVID-19 in Spain is
also more pronounced than Italy and Germany.
