Your browser doesn't support javascript.
loading
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.
Afiliación
  • 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 en 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.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Cell Rep Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: SARS-CoV-2 / COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Cell Rep Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos