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Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health threat. This study aims to evaluate the effect of virus mutation activities and policy interventions on COVID-19 transmissibility in Hong Kong. METHODS: In this study, we integrated the genetic activities o...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813191/ https://www.ncbi.nlm.nih.gov/pubmed/35167995 http://dx.doi.org/10.1016/j.jiph.2022.01.020 |
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author | Lou, Jingzhi Zheng, Hong Zhao, Shi Cao, Lirong Wong, Eliza LY Chen, Zigui Chan, Renee WY Chong, Marc KC Zee, Benny CY Chan, Paul KS Yeoh, Eng-kiong Wang, Maggie H |
author_facet | Lou, Jingzhi Zheng, Hong Zhao, Shi Cao, Lirong Wong, Eliza LY Chen, Zigui Chan, Renee WY Chong, Marc KC Zee, Benny CY Chan, Paul KS Yeoh, Eng-kiong Wang, Maggie H |
author_sort | Lou, Jingzhi |
collection | PubMed |
description | BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health threat. This study aims to evaluate the effect of virus mutation activities and policy interventions on COVID-19 transmissibility in Hong Kong. METHODS: In this study, we integrated the genetic activities of multiple proteins, and quantified the effect of government interventions and mutation activities against the time-varying effective reproduction number R(t). FINDINGS: We found a significantly positive relationship between R(t) and mutation activities and a significantly negative relationship between R(t) and government interventions. The results showed that the mutations that contributed most to the increase of R(t) were from the spike, nucleocapsid and ORF1b genes. Policy of prohibition on group gathering was estimated to have the largest impact on mitigating virus transmissibility. The model explained 63.2% of the R(t) variability with the R(2). CONCLUSION: Our study provided a convenient framework to estimate the effect of genetic contribution and government interventions on pathogen transmissibility. We showed that the S, N and ORF1b protein had significant contribution to the increase of transmissibility of SARS-CoV-2 in Hong Kong, while restrictions of public gathering and suspension of face-to-face class are the most effective government interventions strategies. |
format | Online Article Text |
id | pubmed-8813191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88131912022-02-04 Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic Lou, Jingzhi Zheng, Hong Zhao, Shi Cao, Lirong Wong, Eliza LY Chen, Zigui Chan, Renee WY Chong, Marc KC Zee, Benny CY Chan, Paul KS Yeoh, Eng-kiong Wang, Maggie H J Infect Public Health Original Article BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has become a major public health threat. This study aims to evaluate the effect of virus mutation activities and policy interventions on COVID-19 transmissibility in Hong Kong. METHODS: In this study, we integrated the genetic activities of multiple proteins, and quantified the effect of government interventions and mutation activities against the time-varying effective reproduction number R(t). FINDINGS: We found a significantly positive relationship between R(t) and mutation activities and a significantly negative relationship between R(t) and government interventions. The results showed that the mutations that contributed most to the increase of R(t) were from the spike, nucleocapsid and ORF1b genes. Policy of prohibition on group gathering was estimated to have the largest impact on mitigating virus transmissibility. The model explained 63.2% of the R(t) variability with the R(2). CONCLUSION: Our study provided a convenient framework to estimate the effect of genetic contribution and government interventions on pathogen transmissibility. We showed that the S, N and ORF1b protein had significant contribution to the increase of transmissibility of SARS-CoV-2 in Hong Kong, while restrictions of public gathering and suspension of face-to-face class are the most effective government interventions strategies. The Author(s). Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. 2022-03 2022-02-04 /pmc/articles/PMC8813191/ /pubmed/35167995 http://dx.doi.org/10.1016/j.jiph.2022.01.020 Text en © 2022 The Author(s) 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 | Original Article Lou, Jingzhi Zheng, Hong Zhao, Shi Cao, Lirong Wong, Eliza LY Chen, Zigui Chan, Renee WY Chong, Marc KC Zee, Benny CY Chan, Paul KS Yeoh, Eng-kiong Wang, Maggie H Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title | Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title_full | Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title_fullStr | Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title_full_unstemmed | Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title_short | Quantifying the effect of government interventions and virus mutations on transmission advantage during COVID-19 pandemic |
title_sort | quantifying the effect of government interventions and virus mutations on transmission advantage during covid-19 pandemic |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813191/ https://www.ncbi.nlm.nih.gov/pubmed/35167995 http://dx.doi.org/10.1016/j.jiph.2022.01.020 |
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