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Genomic epidemiology and phylodynamics for county-to-county transmission of SARS-CoV-2 in Minnesota, from 19A to Omicron
Matthew Scotch; Kimberly Lauer; Eric D Wieben; Yesesri Cherukuri; Julie M Cunningham; Eric W Klee; Jonathan J Harrington; Julie S Lau; Samantha J McDonough; Mark Mutawe; John C O'Horo; Chad E Rentmeester; Nicole R Schlicher; Valerie T White; Susan K Schneider; Peter T Vedell; Xiong Wang; Joseph D Yao; Bobbi S Pritt; Andrew P Norgan.
Afiliación
  • Matthew Scotch; Arizona State University
  • Kimberly Lauer; Mayo Clinic
  • Eric D Wieben; Mayo Clinic
  • Yesesri Cherukuri; Mayo Clinic
  • Julie M Cunningham; Mayo Clinic
  • Eric W Klee; Mayo Clinic
  • Jonathan J Harrington; Mayo Clinic
  • Julie S Lau; Mayo Clinic
  • Samantha J McDonough; Mayo Clinic
  • Mark Mutawe; Mayo Clinic
  • John C O'Horo; Mayo Clinic
  • Chad E Rentmeester; Mayo Clinic
  • Nicole R Schlicher; Mayo Clinic
  • Valerie T White; Mayo Clinic
  • Susan K Schneider; Mayo Clinic
  • Peter T Vedell; Mayo Clinic
  • Xiong Wang; Minnesota Department of Health
  • Joseph D Yao; Mayo Clinic
  • Bobbi S Pritt; Mayo Clinic
  • Andrew P Norgan; Mayo Clinic
Preprint en En | PREPRINT-MEDRXIV | ID: ppmedrxiv-22277978
ABSTRACT
SARS-CoV-2 has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of the evolution and spread of pathogens and to inform policy decisions. Most efforts have focused on international or country-wide transmission, which are unable to highlight state-wide trends. We sequenced virus genomes from over 22,000 patients tested at Mayo Clinic Laboratories between 2020-2022 and leveraged detailed patient metadata to describe county-to-county spread in Minnesota. Our findings indicate that spread in the state was mostly dominated by viruses from Hennepin County, which contains the largest metropolis. For many counties, we found that state government restrictions eventually led to a decrease in the diversity of circulating viruses from other counties and that their complete removal in May of 2021 saw a drastic revert to levels at or greater than those observed during the months before. We also linked over 14,000 genomes with patient risk characteristics and infection-related phenotypes from the Mayo Clinic electronic health record. We found that the genetic relationship of Omicron viruses was structured by clinical outcomes when stratifying by patient risk factor and variant of concern. However, we were unable to identify nucleotide variants that drove this association.
Licencia
cc_by_nc_nd
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-MEDRXIV Tipo de estudio: Observational_studies / Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Preprint