Incidence rate estimation of SARS-COVID-19 via a Polya process scheme: a comparative analysis in Italy and European countries

Abstract

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 through a probabilistic Polya urn scheme. Adopting a Polya framework, we provided 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 also 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.