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Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China
Although novel coronavirus pneumonia (COVID-19) was widely spread in mainland China in early 2020, it was soon controlled. To study the impact of government interventions on the spread of disease during epidemics, a differential equation system is established to simulate the process of virus propaga...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459705/ https://www.ncbi.nlm.nih.gov/pubmed/34584515 http://dx.doi.org/10.1007/s12190-021-01611-z |
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author | Guo, Youming Li, Tingting |
author_facet | Guo, Youming Li, Tingting |
author_sort | Guo, Youming |
collection | PubMed |
description | Although novel coronavirus pneumonia (COVID-19) was widely spread in mainland China in early 2020, it was soon controlled. To study the impact of government interventions on the spread of disease during epidemics, a differential equation system is established to simulate the process of virus propagation in this paper. We first analyze its basic properties, basic reproduction number [Formula: see text] and existence of equilibria. Then we prove that the disease-free equilibrium (DFE) is Globally Asymptotically Stable when [Formula: see text] is less than 1. Through the analysis of the daily epidemic data from January 10, 2020 to March 11, 2020, combined with the implementation of the national epidemic policy, we divide the whole process into three stages: the first stage (natural state), the second stage (isolation state), the third stage (isolation, detection and treatment). By using the weighted nonlinear least square method to fit the data of three stages, the parameters are obtained, and three basic reproduction numbers are calculated, which are: [Formula: see text] , [Formula: see text] , [Formula: see text] . Sensitivity analysis of threshold parameters and corresponding graphical results were also performed to examine the relative importance of various model parameters to the spread and prevalence of COVID-19. Finally, we simulate the trend of three stages and verify the theory of Global Asymptotic Stability of DFE. The conclusion of this paper proves theoretically that the Chinese government’s epidemic prevention measures are effective in the fight against the spread of COVID-19. This study can not only provide a reference for research methods to simulate COVID-19 transmission in other countries or regions, but also provide recommendations on COVID-19 prevention measures for them. |
format | Online Article Text |
id | pubmed-8459705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-84597052021-09-24 Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China Guo, Youming Li, Tingting J Appl Math Comput Original Research Although novel coronavirus pneumonia (COVID-19) was widely spread in mainland China in early 2020, it was soon controlled. To study the impact of government interventions on the spread of disease during epidemics, a differential equation system is established to simulate the process of virus propagation in this paper. We first analyze its basic properties, basic reproduction number [Formula: see text] and existence of equilibria. Then we prove that the disease-free equilibrium (DFE) is Globally Asymptotically Stable when [Formula: see text] is less than 1. Through the analysis of the daily epidemic data from January 10, 2020 to March 11, 2020, combined with the implementation of the national epidemic policy, we divide the whole process into three stages: the first stage (natural state), the second stage (isolation state), the third stage (isolation, detection and treatment). By using the weighted nonlinear least square method to fit the data of three stages, the parameters are obtained, and three basic reproduction numbers are calculated, which are: [Formula: see text] , [Formula: see text] , [Formula: see text] . Sensitivity analysis of threshold parameters and corresponding graphical results were also performed to examine the relative importance of various model parameters to the spread and prevalence of COVID-19. Finally, we simulate the trend of three stages and verify the theory of Global Asymptotic Stability of DFE. The conclusion of this paper proves theoretically that the Chinese government’s epidemic prevention measures are effective in the fight against the spread of COVID-19. This study can not only provide a reference for research methods to simulate COVID-19 transmission in other countries or regions, but also provide recommendations on COVID-19 prevention measures for them. Springer Berlin Heidelberg 2021-09-23 2022 /pmc/articles/PMC8459705/ /pubmed/34584515 http://dx.doi.org/10.1007/s12190-021-01611-z Text en © Korean Society for Informatics and Computational Applied Mathematics 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Guo, Youming Li, Tingting Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title | Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title_full | Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title_fullStr | Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title_full_unstemmed | Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title_short | Modeling and dynamic analysis of novel coronavirus pneumonia (COVID-19) in China |
title_sort | modeling and dynamic analysis of novel coronavirus pneumonia (covid-19) in china |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459705/ https://www.ncbi.nlm.nih.gov/pubmed/34584515 http://dx.doi.org/10.1007/s12190-021-01611-z |
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