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Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic
This work systematically conducts a data analysis based on the numbers of both cumulative and daily confirmed COVID-19 cases and deaths in a time span through April 2020 to June 2022 for over 200 countries around the world. Such research feature aims to reveal the temporal and spatial evolution of t...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233890/ https://www.ncbi.nlm.nih.gov/pubmed/35783919 http://dx.doi.org/10.1016/j.physa.2022.127837 |
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author | Liu, Peng Zheng, Yanyan |
author_facet | Liu, Peng Zheng, Yanyan |
author_sort | Liu, Peng |
collection | PubMed |
description | This work systematically conducts a data analysis based on the numbers of both cumulative and daily confirmed COVID-19 cases and deaths in a time span through April 2020 to June 2022 for over 200 countries around the world. Such research feature aims to reveal the temporal and spatial evolution of the country-level distribution observed in COVID-19 pandemic, and obtains some interesting results as follows. (1) The distributions of the numbers for cumulative confirmed cases and deaths obey power-law in early stages of COVID-19 and stretched exponential function in subsequent course. (2) The distributions of the numbers for daily confirmed cases and deaths obey power-law in early and late stages of COVID-19 and stretched exponential function in middle stages. The crossover region between power-law and stretched exponential behavior seems to depend on the evolution of “infection” event and “death” event. Such observation implies a kind of important symmetry related to the dynamics process of COVID-19 spreading. (3) The distributions of the normalized numbers for each metric show a temporal scaling behavior in 2-year period, and are well described by stretched exponential function. The observation of power-law and stretched exponential behavior in such country-level distributions suggests underlying intrinsic dynamics of a virus spreading process in human interconnected society. And thus it is important for understanding and mathematically modeling the COVID-19 pandemic. |
format | Online Article Text |
id | pubmed-9233890 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92338902022-06-27 Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic Liu, Peng Zheng, Yanyan Physica A Article This work systematically conducts a data analysis based on the numbers of both cumulative and daily confirmed COVID-19 cases and deaths in a time span through April 2020 to June 2022 for over 200 countries around the world. Such research feature aims to reveal the temporal and spatial evolution of the country-level distribution observed in COVID-19 pandemic, and obtains some interesting results as follows. (1) The distributions of the numbers for cumulative confirmed cases and deaths obey power-law in early stages of COVID-19 and stretched exponential function in subsequent course. (2) The distributions of the numbers for daily confirmed cases and deaths obey power-law in early and late stages of COVID-19 and stretched exponential function in middle stages. The crossover region between power-law and stretched exponential behavior seems to depend on the evolution of “infection” event and “death” event. Such observation implies a kind of important symmetry related to the dynamics process of COVID-19 spreading. (3) The distributions of the normalized numbers for each metric show a temporal scaling behavior in 2-year period, and are well described by stretched exponential function. The observation of power-law and stretched exponential behavior in such country-level distributions suggests underlying intrinsic dynamics of a virus spreading process in human interconnected society. And thus it is important for understanding and mathematically modeling the COVID-19 pandemic. Elsevier B.V. 2022-10-01 2022-06-26 /pmc/articles/PMC9233890/ /pubmed/35783919 http://dx.doi.org/10.1016/j.physa.2022.127837 Text en © 2022 Elsevier B.V. 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 Liu, Peng Zheng, Yanyan Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title | Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title_full | Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title_fullStr | Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title_full_unstemmed | Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title_short | Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic |
title_sort | temporal and spatial evolution of the distribution related to the number of covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9233890/ https://www.ncbi.nlm.nih.gov/pubmed/35783919 http://dx.doi.org/10.1016/j.physa.2022.127837 |
work_keys_str_mv | AT liupeng temporalandspatialevolutionofthedistributionrelatedtothenumberofcovid19pandemic AT zhengyanyan temporalandspatialevolutionofthedistributionrelatedtothenumberofcovid19pandemic |