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Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram

The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induc...

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Autores principales: Gonçalves, Alan D.S., Fernandes, Leonardo H.S., Nascimento, Abraão D.C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier Ltd. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464589/
https://www.ncbi.nlm.nih.gov/pubmed/36118941
http://dx.doi.org/10.1016/j.chaos.2022.112634
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author Gonçalves, Alan D.S.
Fernandes, Leonardo H.S.
Nascimento, Abraão D.C.
author_facet Gonçalves, Alan D.S.
Fernandes, Leonardo H.S.
Nascimento, Abraão D.C.
author_sort Gonçalves, Alan D.S.
collection PubMed
description The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induced by the well-known Pearson diagram based on multivariate kurtosis and skewness measures to analyze the dynamics of deaths from COVID-19. In particular, we combine bootstrap for time series with SARIMA modeling in a new paradigm to construct a map on which one can analyze the dynamics of a set of time series. The proposed map allows a risk analysis of multiple countries in the four different periods of the pandemic COVID-19 in 55 countries. Our empirical evidence suggests a direct relationship between the multivariate skewness and kurtosis. We observe that the multivariate kurtosis increase leads to the rise of the multivariate skewness. Our findings reveal that the countries with high risk from the behavior of the number of deaths tend to have pronounced skewness and kurtosis values.
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spelling pubmed-94645892022-09-12 Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram Gonçalves, Alan D.S. Fernandes, Leonardo H.S. Nascimento, Abraão D.C. Chaos Solitons Fractals Article The pandemic COVID-19 brings with it the need for studies and tools to help those in charge make decisions. Working with classical time series methods such as ARIMA and SARIMA has shown promising results in the first studies of COVID-19. We advance in this branch by proposing a risk factor map induced by the well-known Pearson diagram based on multivariate kurtosis and skewness measures to analyze the dynamics of deaths from COVID-19. In particular, we combine bootstrap for time series with SARIMA modeling in a new paradigm to construct a map on which one can analyze the dynamics of a set of time series. The proposed map allows a risk analysis of multiple countries in the four different periods of the pandemic COVID-19 in 55 countries. Our empirical evidence suggests a direct relationship between the multivariate skewness and kurtosis. We observe that the multivariate kurtosis increase leads to the rise of the multivariate skewness. Our findings reveal that the countries with high risk from the behavior of the number of deaths tend to have pronounced skewness and kurtosis values. Published by Elsevier Ltd. 2022-11 2022-09-12 /pmc/articles/PMC9464589/ /pubmed/36118941 http://dx.doi.org/10.1016/j.chaos.2022.112634 Text en © 2022 Published by Elsevier Ltd. 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
Gonçalves, Alan D.S.
Fernandes, Leonardo H.S.
Nascimento, Abraão D.C.
Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title_full Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title_fullStr Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title_full_unstemmed Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title_short Dynamics diagnosis of the COVID-19 deaths using the Pearson diagram
title_sort dynamics diagnosis of the covid-19 deaths using the pearson diagram
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464589/
https://www.ncbi.nlm.nih.gov/pubmed/36118941
http://dx.doi.org/10.1016/j.chaos.2022.112634
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