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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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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. |
format | Online Article Text |
id | pubmed-8070306 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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