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A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US

COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic...

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Autores principales: Gao, Shasha, Shen, Mingwang, Wang, Xueying, Wang, Jin, Martcheva, Maia, Rong, Libin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027298/
https://www.ncbi.nlm.nih.gov/pubmed/36940811
http://dx.doi.org/10.1016/j.jtbi.2023.111468
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author Gao, Shasha
Shen, Mingwang
Wang, Xueying
Wang, Jin
Martcheva, Maia
Rong, Libin
author_facet Gao, Shasha
Shen, Mingwang
Wang, Xueying
Wang, Jin
Martcheva, Maia
Rong, Libin
author_sort Gao, Shasha
collection PubMed
description COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.
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spelling pubmed-100272982023-03-21 A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US Gao, Shasha Shen, Mingwang Wang, Xueying Wang, Jin Martcheva, Maia Rong, Libin J Theor Biol Article COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures. Elsevier Ltd. 2023-05-21 2023-03-20 /pmc/articles/PMC10027298/ /pubmed/36940811 http://dx.doi.org/10.1016/j.jtbi.2023.111468 Text en © 2023 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
Gao, Shasha
Shen, Mingwang
Wang, Xueying
Wang, Jin
Martcheva, Maia
Rong, Libin
A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title_full A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title_fullStr A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title_full_unstemmed A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title_short A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US
title_sort multi-strain model with asymptomatic transmission: application to covid-19 in the us
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027298/
https://www.ncbi.nlm.nih.gov/pubmed/36940811
http://dx.doi.org/10.1016/j.jtbi.2023.111468
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