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Genomic epidemiology reveals transmission patterns and dynamics of SARS-CoV-2 in Aotearoa New Zealand.
Geoghegan, Jemma L; Ren, Xiaoyun; Storey, Matthew; Hadfield, James; Jelley, Lauren; Jefferies, Sarah; Sherwood, Jill; Paine, Shevaun; Huang, Sue; Douglas, Jordan; Mendes, Fábio K; Sporle, Andrew; Baker, Michael G; Murdoch, David R; French, Nigel; Simpson, Colin R; Welch, David; Drummond, Alexei J; Holmes, Edward C; Duchêne, Sebastián; de Ligt, Joep.
  • Geoghegan JL; Department of Microbiology and Immunology, University of Otago, Dunedin, New Zealand. jemma.geoghegan@otago.ac.nz.
  • Ren X; Institute of Environmental Science and Research, Wellington, New Zealand. jemma.geoghegan@otago.ac.nz.
  • Storey M; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Hadfield J; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Jelley L; Fred Hutchinson Cancer Research Centre, Seattle, WA, USA.
  • Jefferies S; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Sherwood J; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Paine S; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Huang S; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Douglas J; Institute of Environmental Science and Research, Wellington, New Zealand.
  • Mendes FK; Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand.
  • Sporle A; Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand.
  • Baker MG; Department of Statistics, University of Auckland, Auckland, New Zealand.
  • Murdoch DR; McDonaldSporle Ltd., Auckland, New Zealand.
  • French N; Department of Public Health, University of Otago, Wellington, New Zealand.
  • Simpson CR; Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand.
  • Welch D; School of Veterinary Science, Massey University, Palmerston North, New Zealand.
  • Drummond AJ; School of Health, Faculty of Health, Victoria University of Wellington, Wellington, New Zealand.
  • Holmes EC; Usher Institute, University of Edinburgh, Edinburgh, UK.
  • Duchêne S; Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand.
  • de Ligt J; Centre for Computational Evolution, School of Computer Science, University of Auckland, Auckland, New Zealand.
Nat Commun ; 11(1): 6351, 2020 12 11.
Article in English | MEDLINE | ID: covidwho-974936
Preprint
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ABSTRACT
New Zealand, a geographically remote Pacific island with easily sealable borders, implemented a nationwide 'lockdown' of all non-essential services to curb the spread of COVID-19. Here, we generate 649 SARS-CoV-2 genome sequences from infected patients in New Zealand with samples collected during the 'first wave', representing 56% of all confirmed cases in this time period. Despite its remoteness, the viruses imported into New Zealand represented nearly all of the genomic diversity sequenced from the global virus population. These data helped to quantify the effectiveness of public health interventions. For example, the effective reproductive number, Re of New Zealand's largest cluster decreased from 7 to 0.2 within the first week of lockdown. Similarly, only 19% of virus introductions into New Zealand resulted in ongoing transmission of more than one additional case. Overall, these results demonstrate the utility of genomic pathogen surveillance to inform public health and disease mitigation.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome, Viral / Genomics / SARS-CoV-2 / COVID-19 Type of study: Observational study / Randomized controlled trials Limits: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Country/Region as subject: Oceania Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2020 Document Type: Article Affiliation country: S41467-020-20235-8

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Genome, Viral / Genomics / SARS-CoV-2 / COVID-19 Type of study: Observational study / Randomized controlled trials Limits: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Country/Region as subject: Oceania Language: English Journal: Nat Commun Journal subject: Biology / Science Year: 2020 Document Type: Article Affiliation country: S41467-020-20235-8