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Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers

New variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high effective reproduction numbers are continuously being selected by natural selection. To establish effective control measures for new variants, it is crucial to know their transmissibility and replacement traje...

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Detalles Bibliográficos
Autores principales: Piantham, Chayada, Ito, Kimihito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697243/
https://www.ncbi.nlm.nih.gov/pubmed/36423165
http://dx.doi.org/10.3390/v14112556
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author Piantham, Chayada
Ito, Kimihito
author_facet Piantham, Chayada
Ito, Kimihito
author_sort Piantham, Chayada
collection PubMed
description New variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high effective reproduction numbers are continuously being selected by natural selection. To establish effective control measures for new variants, it is crucial to know their transmissibility and replacement trajectory in advance. In this paper, we conduct retrospective prediction tests for the variant replacement from Alpha to Delta in England, using the relative reproduction numbers of Delta with respect to Alpha estimated from partial observations. We found that once Delta’s relative frequency reached 0.15, the date when the relative frequency of Delta would reach 0.90 was predicted with maximum absolute prediction errors of three days. This means that the time course of the variant replacement could be accurately predicted from early observations. Together with the estimated relative reproduction number of a new variant with respect to old variants, the predicted replacement timing will be crucial information for planning control strategies against the new variant.
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spelling pubmed-96972432022-11-26 Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers Piantham, Chayada Ito, Kimihito Viruses Article New variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high effective reproduction numbers are continuously being selected by natural selection. To establish effective control measures for new variants, it is crucial to know their transmissibility and replacement trajectory in advance. In this paper, we conduct retrospective prediction tests for the variant replacement from Alpha to Delta in England, using the relative reproduction numbers of Delta with respect to Alpha estimated from partial observations. We found that once Delta’s relative frequency reached 0.15, the date when the relative frequency of Delta would reach 0.90 was predicted with maximum absolute prediction errors of three days. This means that the time course of the variant replacement could be accurately predicted from early observations. Together with the estimated relative reproduction number of a new variant with respect to old variants, the predicted replacement timing will be crucial information for planning control strategies against the new variant. MDPI 2022-11-18 /pmc/articles/PMC9697243/ /pubmed/36423165 http://dx.doi.org/10.3390/v14112556 Text en © 2022 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
Piantham, Chayada
Ito, Kimihito
Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title_full Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title_fullStr Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title_full_unstemmed Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title_short Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers
title_sort predicting the trajectory of replacements of sars-cov-2 variants using relative reproduction numbers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9697243/
https://www.ncbi.nlm.nih.gov/pubmed/36423165
http://dx.doi.org/10.3390/v14112556
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