Phylodynamics reveals the role of human travel and contact tracing in controlling the first wave of COVID-19 in four island nations

Author:

Douglas Jordan12ORCID,Mendes Fábio K13,Bouckaert Remco12,Xie Dong12,Jiménez-Silva Cinthy L13,Swanepoel Christiaan12,de Ligt Joep4,Ren Xiaoyun4,Storey Matt4,Hadfield James5,Simpson Colin R6,Geoghegan Jemma L47ORCID,Drummond Alexei J123,Welch David12ORCID

Affiliation:

1. Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand

2. School of Computer Science, The University of Auckland, Auckland 1010, New Zealand

3. School of Biological Sciences, The University of Auckland, Auckland 1010, New Zealand

4. Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand

5. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington WA 98109-1024, USA

6. School of Health, Victoria University of Wellington, Wellington 6012, New Zealand

7. Department of Microbiology and Immunology, University of Otago, Dunedin 9016, New Zealand

Abstract

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.

Funder

New Zealand Ministry of Health

New Zealand Ministry of Business, Innovation & Employment

Royal Society Te Aparangi

Publisher

Oxford University Press (OUP)

Subject

Virology,Microbiology

Reference66 articles.

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