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Modeling COVID-19 dynamic using a two-strain model with vaccination
Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical mode...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847090/ https://www.ncbi.nlm.nih.gov/pubmed/35185299 http://dx.doi.org/10.1016/j.chaos.2022.111927 |
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author | de León, Ugo Avila-Ponce Avila-Vales, Eric Huang, Kuan-lin |
author_facet | de León, Ugo Avila-Ponce Avila-Vales, Eric Huang, Kuan-lin |
author_sort | de León, Ugo Avila-Ponce |
collection | PubMed |
description | Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number [Formula: see text] and the per day infection, death and recovery rates of each strain in the US pandemic. The model dynamics predicted the rise of the alpha variant and shed light on potential impact of the delta variant in 2021. We obtained the minimum percentage of fully vaccinated individuals to reduce the spread of the variants in combination with other intervention strategies to deaccelerate the rise of a multi-strain pandemic. |
format | Online Article Text |
id | pubmed-8847090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88470902022-02-16 Modeling COVID-19 dynamic using a two-strain model with vaccination de León, Ugo Avila-Ponce Avila-Vales, Eric Huang, Kuan-lin Chaos Solitons Fractals Article Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number [Formula: see text] and the per day infection, death and recovery rates of each strain in the US pandemic. The model dynamics predicted the rise of the alpha variant and shed light on potential impact of the delta variant in 2021. We obtained the minimum percentage of fully vaccinated individuals to reduce the spread of the variants in combination with other intervention strategies to deaccelerate the rise of a multi-strain pandemic. Elsevier Ltd. 2022-04 2022-02-16 /pmc/articles/PMC8847090/ /pubmed/35185299 http://dx.doi.org/10.1016/j.chaos.2022.111927 Text en © 2022 Elsevier Ltd. 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 de León, Ugo Avila-Ponce Avila-Vales, Eric Huang, Kuan-lin Modeling COVID-19 dynamic using a two-strain model with vaccination |
title | Modeling COVID-19 dynamic using a two-strain model with vaccination |
title_full | Modeling COVID-19 dynamic using a two-strain model with vaccination |
title_fullStr | Modeling COVID-19 dynamic using a two-strain model with vaccination |
title_full_unstemmed | Modeling COVID-19 dynamic using a two-strain model with vaccination |
title_short | Modeling COVID-19 dynamic using a two-strain model with vaccination |
title_sort | modeling covid-19 dynamic using a two-strain model with vaccination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847090/ https://www.ncbi.nlm.nih.gov/pubmed/35185299 http://dx.doi.org/10.1016/j.chaos.2022.111927 |
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