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Mathematical Modelling of Virus Spreading in COVID-19
A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R(0)) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) over time (m) are ded...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537511/ https://www.ncbi.nlm.nih.gov/pubmed/37766195 http://dx.doi.org/10.3390/v15091788 |
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author | Luo, Liaofu Lv, Jun |
author_facet | Luo, Liaofu Lv, Jun |
author_sort | Luo, Liaofu |
collection | PubMed |
description | A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R(0)) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) over time (m) are deduced and shown to be in good agreement with experimental data. This model effectively addresses three key issues: (1) inferring the conditions under which virus infections die out for a specific strain given R(0); (2) explaining the occurrence of second waves of infection and developing preventive measures; and (3) understanding the competitive spread of two viruses within a region and devising control strategies. The findings highlight the potential of this simple mathematical framework in comprehensively addressing these challenges. The theoretical insights derived from this model can guide the evaluation of infection wave severity and the formulation of effective strategies for controlling and mitigating epidemic outbreaks. |
format | Online Article Text |
id | pubmed-10537511 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105375112023-09-29 Mathematical Modelling of Virus Spreading in COVID-19 Luo, Liaofu Lv, Jun Viruses Article A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R(0)) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) over time (m) are deduced and shown to be in good agreement with experimental data. This model effectively addresses three key issues: (1) inferring the conditions under which virus infections die out for a specific strain given R(0); (2) explaining the occurrence of second waves of infection and developing preventive measures; and (3) understanding the competitive spread of two viruses within a region and devising control strategies. The findings highlight the potential of this simple mathematical framework in comprehensively addressing these challenges. The theoretical insights derived from this model can guide the evaluation of infection wave severity and the formulation of effective strategies for controlling and mitigating epidemic outbreaks. MDPI 2023-08-23 /pmc/articles/PMC10537511/ /pubmed/37766195 http://dx.doi.org/10.3390/v15091788 Text en © 2023 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 Luo, Liaofu Lv, Jun Mathematical Modelling of Virus Spreading in COVID-19 |
title | Mathematical Modelling of Virus Spreading in COVID-19 |
title_full | Mathematical Modelling of Virus Spreading in COVID-19 |
title_fullStr | Mathematical Modelling of Virus Spreading in COVID-19 |
title_full_unstemmed | Mathematical Modelling of Virus Spreading in COVID-19 |
title_short | Mathematical Modelling of Virus Spreading in COVID-19 |
title_sort | mathematical modelling of virus spreading in covid-19 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537511/ https://www.ncbi.nlm.nih.gov/pubmed/37766195 http://dx.doi.org/10.3390/v15091788 |
work_keys_str_mv | AT luoliaofu mathematicalmodellingofvirusspreadingincovid19 AT lvjun mathematicalmodellingofvirusspreadingincovid19 |