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Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants

Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estima...

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Autores principales: Petrone, Mary E, Lucas, Carolina, Menasche, Bridget, Breban, Mallery I, Yildirim, Inci, Campbell, Melissa, Omer, Saad B, Holmes, Edward C, Ko, Albert I, Grubaugh, Nathan D, Iwasaki, Akiko, Wilen, Craig B, Vogels, Chantal B F, Fauver, Joseph R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113931/
https://www.ncbi.nlm.nih.gov/pubmed/36974986
http://dx.doi.org/10.1093/gbe/evad052
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author Petrone, Mary E
Lucas, Carolina
Menasche, Bridget
Breban, Mallery I
Yildirim, Inci
Campbell, Melissa
Omer, Saad B
Holmes, Edward C
Ko, Albert I
Grubaugh, Nathan D
Iwasaki, Akiko
Wilen, Craig B
Vogels, Chantal B F
Fauver, Joseph R
author_facet Petrone, Mary E
Lucas, Carolina
Menasche, Bridget
Breban, Mallery I
Yildirim, Inci
Campbell, Melissa
Omer, Saad B
Holmes, Edward C
Ko, Albert I
Grubaugh, Nathan D
Iwasaki, Akiko
Wilen, Craig B
Vogels, Chantal B F
Fauver, Joseph R
author_sort Petrone, Mary E
collection PubMed
description Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating lineages. In this study, we analyze differences in reporting delays among SARS-CoV-2 VOCs as a plausible explanation for the timing of the global response to the former VOC Mu. Mu likely emerged in South America in mid-2020, where its circulation was largely confined. In this study, we demonstrate that Mu was designated as a VOC ∼1 year after it emerged and find that the reporting of genomic data for Mu differed significantly than that of other VOCs within countries, states, and individual laboratories. Our findings suggest that nonsystematic biases in the reporting of genomic data may have delayed the global response to Mu. Until they are resolved, the surveillance gaps that affected the global response to Mu could impede the rapid and accurate assessment of future emerging variants.
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spelling pubmed-101139312023-04-20 Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants Petrone, Mary E Lucas, Carolina Menasche, Bridget Breban, Mallery I Yildirim, Inci Campbell, Melissa Omer, Saad B Holmes, Edward C Ko, Albert I Grubaugh, Nathan D Iwasaki, Akiko Wilen, Craig B Vogels, Chantal B F Fauver, Joseph R Genome Biol Evol Article Developing a timely and effective response to emerging SARS-CoV-2 variants of concern (VOCs) is of paramount public health importance. Global health surveillance does not rely on genomic data alone to identify concerning variants when they emerge. Instead, methods that utilize genomic data to estimate the epidemiological dynamics of emerging lineages have the potential to serve as an early warning system. However, these methods assume that genomic data are uniformly reported across circulating lineages. In this study, we analyze differences in reporting delays among SARS-CoV-2 VOCs as a plausible explanation for the timing of the global response to the former VOC Mu. Mu likely emerged in South America in mid-2020, where its circulation was largely confined. In this study, we demonstrate that Mu was designated as a VOC ∼1 year after it emerged and find that the reporting of genomic data for Mu differed significantly than that of other VOCs within countries, states, and individual laboratories. Our findings suggest that nonsystematic biases in the reporting of genomic data may have delayed the global response to Mu. Until they are resolved, the surveillance gaps that affected the global response to Mu could impede the rapid and accurate assessment of future emerging variants. Oxford University Press 2023-03-28 /pmc/articles/PMC10113931/ /pubmed/36974986 http://dx.doi.org/10.1093/gbe/evad052 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Petrone, Mary E
Lucas, Carolina
Menasche, Bridget
Breban, Mallery I
Yildirim, Inci
Campbell, Melissa
Omer, Saad B
Holmes, Edward C
Ko, Albert I
Grubaugh, Nathan D
Iwasaki, Akiko
Wilen, Craig B
Vogels, Chantal B F
Fauver, Joseph R
Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title_full Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title_fullStr Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title_full_unstemmed Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title_short Nonsystematic Reporting Biases of the SARS-CoV-2 Variant Mu Could Impact Our Understanding of the Epidemiological Dynamics of Emerging Variants
title_sort nonsystematic reporting biases of the sars-cov-2 variant mu could impact our understanding of the epidemiological dynamics of emerging variants
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113931/
https://www.ncbi.nlm.nih.gov/pubmed/36974986
http://dx.doi.org/10.1093/gbe/evad052
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