The distribution of COVID-19 mortality

We estimate the distribution of COVID-19 mortality (measured as daily deaths) from the start of the pandemic until July 31st, 2022, for six European countries and the USA. We use the Pareto, the stretched exponential, the log-normal and the log-logistic distributions as well as mixtures of the log-n...

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Autores principales: Campolieti, Michele, Ramos, Arturo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674562/
https://www.ncbi.nlm.nih.gov/pubmed/36438695
http://dx.doi.org/10.1016/j.idm.2022.11.003
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author Campolieti, Michele
Ramos, Arturo
author_facet Campolieti, Michele
Ramos, Arturo
author_sort Campolieti, Michele
collection PubMed
description We estimate the distribution of COVID-19 mortality (measured as daily deaths) from the start of the pandemic until July 31st, 2022, for six European countries and the USA. We use the Pareto, the stretched exponential, the log-normal and the log-logistic distributions as well as mixtures of the log-normal and log-logistic distributions. The main results are that the Pareto does not describe well the data and that mixture distributions tend to offer a very good fit to the data. We also compute Value-at-Risk measures as well as mortality probabilities with our estimates. We also discuss the implications of our results and findings from the point of view of public health planning and modelling.
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spelling pubmed-96745622022-11-21 The distribution of COVID-19 mortality Campolieti, Michele Ramos, Arturo Infect Dis Model Article We estimate the distribution of COVID-19 mortality (measured as daily deaths) from the start of the pandemic until July 31st, 2022, for six European countries and the USA. We use the Pareto, the stretched exponential, the log-normal and the log-logistic distributions as well as mixtures of the log-normal and log-logistic distributions. The main results are that the Pareto does not describe well the data and that mixture distributions tend to offer a very good fit to the data. We also compute Value-at-Risk measures as well as mortality probabilities with our estimates. We also discuss the implications of our results and findings from the point of view of public health planning and modelling. KeAi Publishing 2022-11-19 /pmc/articles/PMC9674562/ /pubmed/36438695 http://dx.doi.org/10.1016/j.idm.2022.11.003 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Campolieti, Michele
Ramos, Arturo
The distribution of COVID-19 mortality
title The distribution of COVID-19 mortality
title_full The distribution of COVID-19 mortality
title_fullStr The distribution of COVID-19 mortality
title_full_unstemmed The distribution of COVID-19 mortality
title_short The distribution of COVID-19 mortality
title_sort distribution of covid-19 mortality
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674562/
https://www.ncbi.nlm.nih.gov/pubmed/36438695
http://dx.doi.org/10.1016/j.idm.2022.11.003
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