Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data

It has been reported by World Health Organization (WHO) that the Covid-19 epidemic due to the Sar Cov-2 virus, which started in China and affected the whole world, caused the death of approximately six million people over three years. Global disasters such as pandemics not only cause deaths but also...

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Main Authors: Ekrem Aydıner, Erkan Yılmaz
Format: Article
Language:English
Published: Akif AKGUL 2024-03-01
Series:Chaos Theory and Applications
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Online Access:https://dergipark.org.tr/en/download/article-file/3663901
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author Ekrem Aydıner
Erkan Yılmaz
author_facet Ekrem Aydıner
Erkan Yılmaz
author_sort Ekrem Aydıner
collection DOAJ
description It has been reported by World Health Organization (WHO) that the Covid-19 epidemic due to the Sar Cov-2 virus, which started in China and affected the whole world, caused the death of approximately six million people over three years. Global disasters such as pandemics not only cause deaths but also bring other global catastrophic problems. Therefore, governments need to perform very serious strategic operations to prevent both infection and death. It is accepted that even if there are vaccines developed against the virus, it will never be possible to predict very complex spread dynamics and reach a spread pattern due to new variants and other parameters. In the present study, four countries: Türkiye, Germany, Italy, and the United Kingdom have been selected since they exhibit similar characteristics in terms of the pandemic’s onset date, wave patterns, measures taken against the outbreak, and the vaccines used. Additionally, they are all located on the same continent. For these reasons, the three-year Covid-19 data of these countries were analyzed. Detailed chaotic attractors analyses were performed for each country and Lyapunov exponents were obtained. We showed that the three-year times series is chaotic for the chosen countries. In this sense, our results are compatible with the results of the Covid-19 analysis results in the literature. However, unlike previous Covid-19 studies, we also found out that there are chaotic, periodic, or quasi-periodic sub-series within these chaotic time series. The obtained results are of great importance in terms of revealing the details of the dynamics of the pandemic.
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spelling doaj-art-0e678a5fb78c49a6a8bb711099fbe09b2025-01-23T18:20:09ZengAkif AKGULChaos Theory and Applications2687-45392024-03-0161415010.51537/chaos.14207241971Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality DataEkrem Aydıner0https://orcid.org/0000-0002-0385-9916Erkan Yılmaz1https://orcid.org/0000-0002-5823-6134İstanbul ÜniversitesiISTANBUL UNIVERSITY, INSTITUTE OF SCIENCEIt has been reported by World Health Organization (WHO) that the Covid-19 epidemic due to the Sar Cov-2 virus, which started in China and affected the whole world, caused the death of approximately six million people over three years. Global disasters such as pandemics not only cause deaths but also bring other global catastrophic problems. Therefore, governments need to perform very serious strategic operations to prevent both infection and death. It is accepted that even if there are vaccines developed against the virus, it will never be possible to predict very complex spread dynamics and reach a spread pattern due to new variants and other parameters. In the present study, four countries: Türkiye, Germany, Italy, and the United Kingdom have been selected since they exhibit similar characteristics in terms of the pandemic’s onset date, wave patterns, measures taken against the outbreak, and the vaccines used. Additionally, they are all located on the same continent. For these reasons, the three-year Covid-19 data of these countries were analyzed. Detailed chaotic attractors analyses were performed for each country and Lyapunov exponents were obtained. We showed that the three-year times series is chaotic for the chosen countries. In this sense, our results are compatible with the results of the Covid-19 analysis results in the literature. However, unlike previous Covid-19 studies, we also found out that there are chaotic, periodic, or quasi-periodic sub-series within these chaotic time series. The obtained results are of great importance in terms of revealing the details of the dynamics of the pandemic.https://dergipark.org.tr/en/download/article-file/3663901chaoticquasi-periodiccovid-19largest lyapunovexponenttime delayphase spaceembeddingdimension
spellingShingle Ekrem Aydıner
Erkan Yılmaz
Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
Chaos Theory and Applications
chaotic
quasi-periodic
covid-19
largest lyapunovexponent
time delay
phase space
embeddingdimension
title Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
title_full Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
title_fullStr Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
title_full_unstemmed Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
title_short Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data
title_sort chaotic and quasi periodic regimes in the covid 19 mortality data
topic chaotic
quasi-periodic
covid-19
largest lyapunovexponent
time delay
phase space
embeddingdimension
url https://dergipark.org.tr/en/download/article-file/3663901
work_keys_str_mv AT ekremaydıner chaoticandquasiperiodicregimesinthecovid19mortalitydata
AT erkanyılmaz chaoticandquasiperiodicregimesinthecovid19mortalitydata