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Combining genomic data and infection estimates to characterize the complex dynamics of SARS-CoV-2 Omicron variants in the US.
Lopes, Rafael; Pham, Kien; Klaassen, Fayette; Chitwood, Melanie H; Hahn, Anne M; Redmond, Seth; Swartwood, Nicole A; Salomon, Joshua A; Menzies, Nicolas A; Cohen, Ted; Grubaugh, Nathan D.
Afiliação
  • Lopes R; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA. Electronic address: rafael.lopes@yale.edu.
  • Pham K; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
  • Klaassen F; Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
  • Chitwood MH; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
  • Hahn AM; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
  • Redmond S; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
  • Swartwood NA; Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
  • Salomon JA; Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA.
  • Menzies NA; Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
  • Cohen T; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA. Electronic address: theodore.cohen@yale.edu.
  • Grubaugh ND; Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA. Electronic address: nathan.grubaugh@yale.edu.
Cell Rep ; 43(7): 114451, 2024 Jul 23.
Article em En | MEDLINE | ID: mdl-38970788
ABSTRACT
Omicron surged as a variant of concern in late 2021. Several distinct Omicron variants appeared and overtook each other. We combined variant frequencies and infection estimates from a nowcasting model for each US state to estimate variant-specific infections, attack rates, and effective reproduction numbers (Rt). BA.1 rapidly emerged, and we estimate that it infected 47.7% of the US population before it was replaced by BA.2. We estimate that BA.5 infected 35.7% of the US population, persisting in circulation for nearly 6 months. Other variants-BA.2, BA.4, and XBB-together infected 30.7% of the US population. We found a positive correlation between the state-level BA.1 attack rate and social vulnerability and a negative correlation between the BA.1 and BA.2 attack rates. Our findings illustrate the complex interplay between viral evolution, population susceptibility, and social factors during the Omicron emergence in the US.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Cell Rep Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans País/Região como assunto: America do norte Idioma: En Revista: Cell Rep Ano de publicação: 2024 Tipo de documento: Article