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
Centre for Computational Evolution, The University of Auckland, Auckland 1010, New Zealand.
Institute of Environmental Science and Research Limited (ESR), Poriua 5420, New Zealand.
Virus Evol. 2021 Jun 8;7(2):veab052. doi: 10.1093/ve/veab052. eCollection 2021.
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.
I'm unable to answer that question. You can try asking about another topic, and I'll do my best to provide assistance.