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Phylodynamics reveals the role of human travel and contact tracing in controlling the first wave of COVID-19 in four island nations.
Douglas, Jordan; Mendes, Fábio K; Bouckaert, Remco; Xie, Dong; Jiménez-Silva, Cinthy L; Swanepoel, Christiaan; de Ligt, Joep; Ren, Xiaoyun; Storey, Matt; Hadfield, James; Simpson, Colin R; Geoghegan, Jemma L; Drummond, Alexei J; Welch, David.
  • Douglas J; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Mendes FK; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Bouckaert R; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Xie D; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Jiménez-Silva CL; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Swanepoel C; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • de Ligt J; Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand.
  • Ren X; Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand.
  • Storey M; Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand.
  • Hadfield J; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington WA 98109-1024, USA.
  • Simpson CR; School of Health, Victoria University of Wellington, Wellington 6012, New Zealand.
  • Geoghegan JL; Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand.
  • Drummond AJ; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
  • Welch D; Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
Virus Evol ; 7(2): veab052, 2021.
Article in English | MEDLINE | ID: covidwho-1412220
ABSTRACT
New Zealand, Australia, Iceland, and Taiwan all saw success in controlling their first waves of Coronavirus Disease 2019 (COVID-19). As islands, they make excellent case studies for exploring the effects of international travel and human movement on the spread of COVID-19. We employed a range of robust phylodynamic methods and genome subsampling strategies to infer the epidemiological history of Severe acute respiratory syndrome coronavirus 2 in these four countries. We compared these results to transmission clusters identified by the New Zealand Ministry of Health by contact tracing strategies. We estimated the effective reproduction number of COVID-19 as 1-1.4 during early stages of the pandemic and show that it declined below 1 as human movement was restricted. We also showed that this disease was introduced many times into each country and that introductions slowed down markedly following the reduction of international travel in mid-March 2020. Finally, we confirmed that New Zealand transmission clusters identified via standard health surveillance strategies largely agree with those defined by genomic data. We have demonstrated how the use of genomic data and computational biology methods can assist health officials in characterising the epidemiology of viral epidemics and for contact tracing.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Virus Evol Year: 2021 Document Type: Article Affiliation country: Ve

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Virus Evol Year: 2021 Document Type: Article Affiliation country: Ve