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Temporal and spatial evolution of the distribution related to the number of COVID-19 pandemic.
Liu, Peng; Zheng, Yanyan.
  • Liu P; School of Information, Xi'an University of Finance and Economics, Xi'an 710100, Shaanxi, PR China.
  • Zheng Y; School of Management, Xi'an Polytechnic University, Xi'an 710048, Shaanxi, PR China.
Physica A ; 603: 127837, 2022 Oct 01.
Article in English | MEDLINE | ID: covidwho-1907661
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Long Covid Language: English Journal: Physica A Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Topics: Long Covid Language: English Journal: Physica A Year: 2022 Document Type: Article