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A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages.
Dellicour, Simon; Durkin, Keith; Hong, Samuel L; Vanmechelen, Bert; Martí-Carreras, Joan; Gill, Mandev S; Meex, Cécile; Bontems, Sébastien; André, Emmanuel; Gilbert, Marius; Walker, Conor; Maio, Nicola De; Faria, Nuno R; Hadfield, James; Hayette, Marie-Pierre; Bours, Vincent; Wawina-Bokalanga, Tony; Artesi, Maria; Baele, Guy; Maes, Piet.
  • Dellicour S; Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.
  • Durkin K; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Hong SL; Department of Human Genetics, CHU Liège, and Medical Genomics, GIGA Research Center, University of Liège, Liège, Belgium.
  • Vanmechelen B; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Martí-Carreras J; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Gill MS; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Meex C; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Bontems S; Department of Clinical Microbiology, University of Liège, Liège, Belgium.
  • André E; Department of Clinical Microbiology, University of Liège, Liège, Belgium.
  • Gilbert M; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Walker C; Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium.
  • Maio N; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.
  • Faria NR; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom.
  • Hadfield J; Department of Zoology, University of Oxford, Oxford, United Kingdom.
  • Hayette MP; MRC Centre for Global Infectious Disease Analysis, J-IDEA, Imperial College London, London, United Kingdom.
  • Bours V; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Wawina-Bokalanga T; Department of Clinical Microbiology, University of Liège, Liège, Belgium.
  • Artesi M; Department of Human Genetics, CHU Liège, and Medical Genomics, GIGA Research Center, University of Liège, Liège, Belgium.
  • Baele G; Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium.
  • Maes P; Department of Human Genetics, CHU Liège, and Medical Genomics, GIGA Research Center, University of Liège, Liège, Belgium.
Mol Biol Evol ; 38(4): 1608-1613, 2021 04 13.
Article in English | MEDLINE | ID: covidwho-900448
Preprint
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ABSTRACT
Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome, Viral / Phylogeography / SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Europa Language: English Journal: Mol Biol Evol Journal subject: Molecular Biology Year: 2021 Document Type: Article Affiliation country: Molbev

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome, Viral / Phylogeography / SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: Europa Language: English Journal: Mol Biol Evol Journal subject: Molecular Biology Year: 2021 Document Type: Article Affiliation country: Molbev