A phenomenological estimate of the true scale of CoViD-19 from primary data

Estimation of the prevalence of undocumented SARS-CoV-2 infections is critical for understanding the overall impact of CoViD-19, and for implementing effective public policy intervention strategies. We discuss a simple yet effective approach to estimate the true number of people infected by SARS-CoV...

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Detalles Bibliográficos
Autores principales: Palatella, Luigi, Vanni, Fabio, Lambert, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955922/
https://www.ncbi.nlm.nih.gov/pubmed/33746372
http://dx.doi.org/10.1016/j.chaos.2021.110854
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author Palatella, Luigi
Vanni, Fabio
Lambert, David
author_facet Palatella, Luigi
Vanni, Fabio
Lambert, David
author_sort Palatella, Luigi
collection PubMed
description Estimation of the prevalence of undocumented SARS-CoV-2 infections is critical for understanding the overall impact of CoViD-19, and for implementing effective public policy intervention strategies. We discuss a simple yet effective approach to estimate the true number of people infected by SARS-CoV-2, using raw epidemiological data reported by official health institutions in the largest EU countries and the USA.
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spelling pubmed-79559222021-03-15 A phenomenological estimate of the true scale of CoViD-19 from primary data Palatella, Luigi Vanni, Fabio Lambert, David Chaos Solitons Fractals Article Estimation of the prevalence of undocumented SARS-CoV-2 infections is critical for understanding the overall impact of CoViD-19, and for implementing effective public policy intervention strategies. We discuss a simple yet effective approach to estimate the true number of people infected by SARS-CoV-2, using raw epidemiological data reported by official health institutions in the largest EU countries and the USA. Elsevier Ltd. 2021-05 2021-03-14 /pmc/articles/PMC7955922/ /pubmed/33746372 http://dx.doi.org/10.1016/j.chaos.2021.110854 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Palatella, Luigi
Vanni, Fabio
Lambert, David
A phenomenological estimate of the true scale of CoViD-19 from primary data
title A phenomenological estimate of the true scale of CoViD-19 from primary data
title_full A phenomenological estimate of the true scale of CoViD-19 from primary data
title_fullStr A phenomenological estimate of the true scale of CoViD-19 from primary data
title_full_unstemmed A phenomenological estimate of the true scale of CoViD-19 from primary data
title_short A phenomenological estimate of the true scale of CoViD-19 from primary data
title_sort phenomenological estimate of the true scale of covid-19 from primary data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955922/
https://www.ncbi.nlm.nih.gov/pubmed/33746372
http://dx.doi.org/10.1016/j.chaos.2021.110854
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