  During an ongoing epidemic, especially in the case of a new agent, data are
partial and sparse, also affected by external factors as for example climatic
effects or preparedness and response capability of healthcare structures.
Despite that we showed how, under some universality assumptions, it is possible
to extract strategic insights by modelling the pandemic trough a probabilistic
Polya urn scheme. In the Polya framework, we provide both the distribution of
infected cases and the asymptotic estimation of the incidence rate, showing
that data are consistent with a general underlying process at different scales.
Using European confirmed cases and diagnostic test data on COVID-19 , we
provided an extensive comparison among European countries and between Europe
and Italy at regional scale, for both the two big waves of infection. We
globally estimated an incidence rate in accordance with previous studies. On
the other hand, this quantity could play a crucial role as a proxy variable for
an unbiased estimation of the real incidence rate, including symptomatic and
asymptomatic cases.
