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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.
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.
  • Petrone ME; Department of Epidemiology of Microbial Diseases, Yale School of Public Health.
  • Lucas C; Sydney Institute for Infectious Diseases, School of Medical Sciences, University of Sydney, NSW, Australia.
  • Menasche B; Department of Immunobiology, Yale University School of Medicine.
  • Breban MI; Department of Laboratory Medicine, Yale University School of Medicine.
  • Yildirim I; Department of Epidemiology of Microbial Diseases, Yale School of Public Health.
  • Campbell M; Department of Epidemiology of Microbial Diseases, Yale School of Public Health.
  • Omer SB; Department of Pediatric, Section of Infectious Diseases and Global Health, Yale University School of Medicine.
  • Holmes EC; Yale Institute for Global Health, Yale University.
  • Ko AI; Department of Medicine, Section of Infectious Diseases, Yale University School of Medicine.
  • Grubaugh ND; Department of Epidemiology of Microbial Diseases, Yale School of Public Health.
  • Iwasaki A; Yale Institute for Global Health, Yale University.
  • Wilen CB; Department of Medicine, Section of Infectious Diseases, Yale University School of Medicine.
  • Vogels CBF; Sydney Institute for Infectious Diseases, School of Medical Sciences, University of Sydney, NSW, Australia.
  • Fauver JR; Department of Epidemiology of Microbial Diseases, Yale School of Public Health.
Genome Biol Evol ; 15(4)2023 04 05.
Article in English | MEDLINE | ID: covidwho-2276330
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Systematic review/Meta Analysis Topics: Variants Limits: Humans Language: English Journal subject: Biology / Molecular Biology Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Systematic review/Meta Analysis Topics: Variants Limits: Humans Language: English Journal subject: Biology / Molecular Biology Year: 2023 Document Type: Article