Browsing by Author "Huang S"

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    Genomic epidemiology of Delta SARS-CoV-2 during transition from elimination to suppression in Aotearoa New Zealand
    (Springer Nature Limited, 2022-07-12) Jelley L; Douglas J; Ren X; Winter D; McNeill A; Huang S; French N; Welch D; Hadfield J; de Ligt J; Geoghegan JL
    New Zealand's COVID-19 elimination strategy heavily relied on the use of genomics to inform contact tracing, linking cases to the border and to clusters during community outbreaks. In August 2021, New Zealand entered its second nationwide lockdown after the detection of a single community case with no immediately apparent epidemiological link to the border. This incursion resulted in the largest outbreak seen in New Zealand caused by the Delta Variant of Concern. Here we generated 3806 high quality SARS-CoV-2 genomes from cases reported in New Zealand between 17 August and 1 December 2021, representing 43% of reported cases. We detected wide geographical spread coupled with undetected community transmission, characterised by the apparent extinction and reappearance of genomically linked clusters. We also identified the emergence, and near replacement, of genomes possessing a 10-nucleotide frameshift deletion that caused the likely truncation of accessory protein ORF7a. By early October, New Zealand moved from an elimination strategy to a suppression strategy and the role of genomics changed markedly from being used to track and trace, towards population-level surveillance.
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    Tracing household transmission of SARS-CoV-2 in New Zealand using genomics
    (Springer Nature Limited, 2024-06-03) Jelley L; Aminisani N; O’Neill M; Jennings T; Douglas J; Utekar S; Johnston H; Welch D; Hadfield J; SHIVERS Investigation Team; de Ligt J; Winter D; French N; Thomas PG; Webby RJ; Huang S; Geoghegan JL
    By early 2022, the highly transmissible Omicron variant of SARS-CoV-2 had spread across most of the world. For the first time since the pandemic began, New Zealand was experiencing high levels of community transmission of SARS-CoV-2. We enroled a cohort of households to better understand differences in transmission dynamics among subvariants of Omicron. We enroled 71 households, comprising 289 participants, and aimed to use viral genomes to gain a clearer understanding of variant-specific differences in epidemiological parameters affecting transmission dynamics. Approximately 80% of the households enroled experienced transmission of BA.2, while most of the remaining households had infections with BA.1 or BA.5. Using a logistic regression generalised linear mixed model, we found no difference in household secondary infection rate between Omicron subvariants BA.1, BA.2 and BA.5. Of the households recruited, the vast majority (92%) experienced a single chain of transmission with one inferred introduction. Further, we found that in 48% of the households studied, all household participants became infected following an index case. Most household participants tested positive within a week following an introduction, supporting the seven-day isolation requirement for household contacts that was in place in New Zealand at the time. By integrating genomic and epidemiological data, we show that viral transmission dynamics can be investigated with a higher level of granularity than with epidemiological data alone. Overall, households are a high risk setting for viral transmission in New Zealand.