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Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2

As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS-CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the pandemic. Characterizing the relationship between mutation activities and the risk of severe clinical outcomes...

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Autores principales: Zhao, Shi, Lou, Jingzhi, Chong, Marc K. C., Cao, Lirong, Zheng, Hong, Chen, Zigui, Chan, Renee W. Y., Zee, Benny C. Y., Chan, Paul K. S., Wang, Maggie H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070306/
https://www.ncbi.nlm.nih.gov/pubmed/33918060
http://dx.doi.org/10.3390/v13040638
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author Zhao, Shi
Lou, Jingzhi
Chong, Marc K. C.
Cao, Lirong
Zheng, Hong
Chen, Zigui
Chan, Renee W. Y.
Zee, Benny C. Y.
Chan, Paul K. S.
Wang, Maggie H.
author_facet Zhao, Shi
Lou, Jingzhi
Chong, Marc K. C.
Cao, Lirong
Zheng, Hong
Chen, Zigui
Chan, Renee W. Y.
Zee, Benny C. Y.
Chan, Paul K. S.
Wang, Maggie H.
author_sort Zhao, Shi
collection PubMed
description As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS-CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the pandemic. Characterizing the relationship between mutation activities and the risk of severe clinical outcomes is of public health importance for informing the healthcare decision-making process. Using a likelihood-based approach, we developed a statistical framework to reconstruct a time-varying and variant-specific case fatality ratio (CFR), and to estimate changes in CFR associated with a single mutation empirically. For illustration, the statistical framework is implemented to the COVID-19 surveillance data in the United Kingdom (UK). The reconstructed instantaneous CFR gradually increased from 1.0% in September to 2.2% in November 2020 and stabilized at this level thereafter, which monitors the mortality risk of COVID-19 on a real-time basis. We identified a link between the SARS-CoV-2 mutation activity at molecular scale and COVID-19 mortality risk at population scale, and found that the 501Y variants may slightly but not significantly increase 18% of fatality risk than the preceding 501N variants. We found no statistically significant evidence of change in COVID-19 mortality risk associated with 501Y variants, and highlighted the real-time estimating potentials of the modelling framework.
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spelling pubmed-80703062021-04-26 Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2 Zhao, Shi Lou, Jingzhi Chong, Marc K. C. Cao, Lirong Zheng, Hong Chen, Zigui Chan, Renee W. Y. Zee, Benny C. Y. Chan, Paul K. S. Wang, Maggie H. Viruses Article As COVID-19 is posing a serious threat to global health, the emerging mutation in SARS-CoV-2 genomes, for example, N501Y substitution, is one of the major challenges against control of the pandemic. Characterizing the relationship between mutation activities and the risk of severe clinical outcomes is of public health importance for informing the healthcare decision-making process. Using a likelihood-based approach, we developed a statistical framework to reconstruct a time-varying and variant-specific case fatality ratio (CFR), and to estimate changes in CFR associated with a single mutation empirically. For illustration, the statistical framework is implemented to the COVID-19 surveillance data in the United Kingdom (UK). The reconstructed instantaneous CFR gradually increased from 1.0% in September to 2.2% in November 2020 and stabilized at this level thereafter, which monitors the mortality risk of COVID-19 on a real-time basis. We identified a link between the SARS-CoV-2 mutation activity at molecular scale and COVID-19 mortality risk at population scale, and found that the 501Y variants may slightly but not significantly increase 18% of fatality risk than the preceding 501N variants. We found no statistically significant evidence of change in COVID-19 mortality risk associated with 501Y variants, and highlighted the real-time estimating potentials of the modelling framework. MDPI 2021-04-08 /pmc/articles/PMC8070306/ /pubmed/33918060 http://dx.doi.org/10.3390/v13040638 Text en © 2021 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
Zhao, Shi
Lou, Jingzhi
Chong, Marc K. C.
Cao, Lirong
Zheng, Hong
Chen, Zigui
Chan, Renee W. Y.
Zee, Benny C. Y.
Chan, Paul K. S.
Wang, Maggie H.
Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title_full Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title_fullStr Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title_full_unstemmed Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title_short Inferring the Association between the Risk of COVID-19 Case Fatality and N501Y Substitution in SARS-CoV-2
title_sort inferring the association between the risk of covid-19 case fatality and n501y substitution in sars-cov-2
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070306/
https://www.ncbi.nlm.nih.gov/pubmed/33918060
http://dx.doi.org/10.3390/v13040638
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