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

Asymptotic Incidence Rate estimation of SARS-COVID-19 via a Polya process scheme: a comparative analysis in Italy and European Countries