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

TL;DR

This paper models COVID-19 incidence rates using a probabilistic Polya urn scheme, providing asymptotic estimates and comparative analysis across Italy and European countries during two infection waves.

Contribution

It introduces a novel Polya process-based approach for estimating COVID-19 incidence rates, accounting for partial and sparse data during an epidemic.

Findings

Estimated incidence rates align with previous studies.

Data are consistent with a universal underlying process.

Comparison reveals differences between countries and infection waves.

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 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.