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

• Published in: Virus Evolution
• Main Authors: 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
• Other Authors: New Zealand Ministry of Health, New Zealand Ministry of Business, Innovation & Employment, Royal Society Te Aparangi
• Format: Article in Journal/Newspaper
• Language: English
• Published: Oxford University Press (OUP) 2021
• Subjects: New Zealand; Iceland
• Online Access: http://dx.doi.org/10.1093/ve/veab052; http://academic.oup.com/ve/advance-article-pdf/doi/10.1093/ve/veab052/38876584/veab052.pdf; https://academic.oup.com/ve/article-pdf/7/2/veab052/50058354/veab052.pdf

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.