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Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework

The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi-directional mutation rate. Many new variants even have an immune-evading property, which means that some individuals with antibod...

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Autores principales: Zhan, Choujun, Zheng, Yufan, Shao, Lujiao, Chen, Guanrong, Zhang, Haijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901228/
https://www.ncbi.nlm.nih.gov/pubmed/36777698
http://dx.doi.org/10.1016/j.ins.2023.02.001
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author Zhan, Choujun
Zheng, Yufan
Shao, Lujiao
Chen, Guanrong
Zhang, Haijun
author_facet Zhan, Choujun
Zheng, Yufan
Shao, Lujiao
Chen, Guanrong
Zhang, Haijun
author_sort Zhan, Choujun
collection PubMed
description The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi-directional mutation rate. Many new variants even have an immune-evading property, which means that some individuals with antibodies against one variant can be reinfected by other variants. As a result, the realistic is still suffering from new waves of COVID-19 by its new variants. How to control the transmission or even eradicate the COVID-19 pandemic remains a critical issue for the whole world. This work presents an epidemiological framework for mimicking the multi-directional mutation process of SARS-CoV-2 and the epidemic spread of COVID-19 under realistic scenarios considering multiple variants. The proposed framework is used to evaluate single and combined public health interventions, which include non-pharmaceutical interventions, pharmaceutical interventions, and vaccine interventions under the existence of multi-directional mutations of SARS-CoV-2. The results suggest that several combined intervention strategies give optimal results and are feasible, requiring only moderate levels of individual interventions. Furthermore, the results indicate that even if the mutation rate of SARS-CoV-2 decreased 100 times, the pandemic would still not be eradicated without appropriate public health interventions.
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spelling pubmed-99012282023-02-07 Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework Zhan, Choujun Zheng, Yufan Shao, Lujiao Chen, Guanrong Zhang, Haijun Inf Sci (N Y) Article The COVID-19 pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a single-stranded positive-stranded RNA virus with a high multi-directional mutation rate. Many new variants even have an immune-evading property, which means that some individuals with antibodies against one variant can be reinfected by other variants. As a result, the realistic is still suffering from new waves of COVID-19 by its new variants. How to control the transmission or even eradicate the COVID-19 pandemic remains a critical issue for the whole world. This work presents an epidemiological framework for mimicking the multi-directional mutation process of SARS-CoV-2 and the epidemic spread of COVID-19 under realistic scenarios considering multiple variants. The proposed framework is used to evaluate single and combined public health interventions, which include non-pharmaceutical interventions, pharmaceutical interventions, and vaccine interventions under the existence of multi-directional mutations of SARS-CoV-2. The results suggest that several combined intervention strategies give optimal results and are feasible, requiring only moderate levels of individual interventions. Furthermore, the results indicate that even if the mutation rate of SARS-CoV-2 decreased 100 times, the pandemic would still not be eradicated without appropriate public health interventions. Elsevier Inc. 2023-05 2023-02-06 /pmc/articles/PMC9901228/ /pubmed/36777698 http://dx.doi.org/10.1016/j.ins.2023.02.001 Text en © 2023 Elsevier Inc. 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
Zhan, Choujun
Zheng, Yufan
Shao, Lujiao
Chen, Guanrong
Zhang, Haijun
Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title_full Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title_fullStr Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title_full_unstemmed Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title_short Modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: A general framework
title_sort modeling the spread dynamics of multiple-variant coronavirus disease under public health interventions: a general framework
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901228/
https://www.ncbi.nlm.nih.gov/pubmed/36777698
http://dx.doi.org/10.1016/j.ins.2023.02.001
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