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The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan
In December 2019, China reported a new virus identified as SARS-CoV-2, causing COVID-19, which soon spread to other countries and led to a global pandemic. Although many countries imposed strict actions to control the spread of the virus, the COVID-19 pandemic resulted in unprecedented economic and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566294/ https://www.ncbi.nlm.nih.gov/pubmed/36232099 http://dx.doi.org/10.3390/ijerph191912804 |
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author | Sapkota, Nabin Murata, Atsuo Karwowski, Waldemar Davahli, Mohammad Reza Fiok, Krzysztof Aljuaid, Awad M. Marek, Tadeusz Ahram, Tareq |
author_facet | Sapkota, Nabin Murata, Atsuo Karwowski, Waldemar Davahli, Mohammad Reza Fiok, Krzysztof Aljuaid, Awad M. Marek, Tadeusz Ahram, Tareq |
author_sort | Sapkota, Nabin |
collection | PubMed |
description | In December 2019, China reported a new virus identified as SARS-CoV-2, causing COVID-19, which soon spread to other countries and led to a global pandemic. Although many countries imposed strict actions to control the spread of the virus, the COVID-19 pandemic resulted in unprecedented economic and social consequences in 2020 and early 2021. To understand the dynamics of the spread of the virus, we evaluated its chaotic behavior in Japan. A 0–1 test was applied to the time-series data of daily COVID-19 cases from January 26, 2020 to August 5, 2021 (3 days before the end of the Tokyo Olympic Games). Additionally, the influence of hosting the Olympic Games in Tokyo was assessed in data including the post-Olympic period until October 8, 2021. Even with these extended time period data, although the time-series data for the daily infections across Japan were not found to be chaotic, more than 76.6% and 55.3% of the prefectures in Japan showed chaotic behavior in the pre- and post-Olympic Games periods, respectively. Notably, Tokyo and Kanagawa, the two most populous cities in Japan, did not show chaotic behavior in their time-series data of daily COVID-19 confirmed cases. Overall, the prefectures with the largest population centers showed non-chaotic behavior, whereas the prefectures with smaller populations showed chaotic behavior. This phenomenon was observed in both of the analyzed time periods (pre- and post-Olympic Games); therefore, more attention should be paid to prefectures with smaller populations, in which controlling and preventing the current pandemic is more difficult. |
format | Online Article Text |
id | pubmed-9566294 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95662942022-10-15 The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan Sapkota, Nabin Murata, Atsuo Karwowski, Waldemar Davahli, Mohammad Reza Fiok, Krzysztof Aljuaid, Awad M. Marek, Tadeusz Ahram, Tareq Int J Environ Res Public Health Article In December 2019, China reported a new virus identified as SARS-CoV-2, causing COVID-19, which soon spread to other countries and led to a global pandemic. Although many countries imposed strict actions to control the spread of the virus, the COVID-19 pandemic resulted in unprecedented economic and social consequences in 2020 and early 2021. To understand the dynamics of the spread of the virus, we evaluated its chaotic behavior in Japan. A 0–1 test was applied to the time-series data of daily COVID-19 cases from January 26, 2020 to August 5, 2021 (3 days before the end of the Tokyo Olympic Games). Additionally, the influence of hosting the Olympic Games in Tokyo was assessed in data including the post-Olympic period until October 8, 2021. Even with these extended time period data, although the time-series data for the daily infections across Japan were not found to be chaotic, more than 76.6% and 55.3% of the prefectures in Japan showed chaotic behavior in the pre- and post-Olympic Games periods, respectively. Notably, Tokyo and Kanagawa, the two most populous cities in Japan, did not show chaotic behavior in their time-series data of daily COVID-19 confirmed cases. Overall, the prefectures with the largest population centers showed non-chaotic behavior, whereas the prefectures with smaller populations showed chaotic behavior. This phenomenon was observed in both of the analyzed time periods (pre- and post-Olympic Games); therefore, more attention should be paid to prefectures with smaller populations, in which controlling and preventing the current pandemic is more difficult. MDPI 2022-10-06 /pmc/articles/PMC9566294/ /pubmed/36232099 http://dx.doi.org/10.3390/ijerph191912804 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sapkota, Nabin Murata, Atsuo Karwowski, Waldemar Davahli, Mohammad Reza Fiok, Krzysztof Aljuaid, Awad M. Marek, Tadeusz Ahram, Tareq The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title | The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title_full | The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title_fullStr | The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title_full_unstemmed | The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title_short | The Chaotic Behavior of the Spread of Infection during the COVID-19 Pandemic in Japan |
title_sort | chaotic behavior of the spread of infection during the covid-19 pandemic in japan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566294/ https://www.ncbi.nlm.nih.gov/pubmed/36232099 http://dx.doi.org/10.3390/ijerph191912804 |
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