A phenomenological estimate of the Covid-19 true scale from primary data
Physics and Society
2022-01-31 v2
Abstract
Estimation of prevalence of undocumented SARS-CoV-2 infections is critical for understanding the overall impact of the Covid-19 disease. In fact, unveiling uncounted cases has fundamental implications for public policy interventions strategies. In the present work, we show a basic yet effective approach to estimate the actual number of people infected by Sars-Cov-2, by using epidemiological raw data reported by official health institutions in the largest EU countries and USA.
Keywords
Cite
@article{arxiv.2101.05381,
title = {A phenomenological estimate of the Covid-19 true scale from primary data},
author = {Luigi Palatella and Fabio Vanni and David Lambert},
journal= {arXiv preprint arXiv:2101.05381},
year = {2022}
}