Browsing by Author "de Ligt J"

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COVID-19 vaccine strategies for Aotearoa New Zealand: a mathematical modelling study
(Elsevier Ltd, 2021-10) Nguyen T; Adnan M; Nguyen BP; de Ligt J; Geoghegan JL; Dean R; Jefferies S; Baker MG; Seah WKG; Sporle AA; French NP; Murdoch DR; Welch D; Simpson CR
Background: COVID-19 elimination measures, including border closures have been applied in New Zealand. We have modelled the potential effect of vaccination programmes for opening borders. Methods: We used a deterministic age-stratified Susceptible, Exposed, Infectious, Recovered (SEIR) model. We minimised spread by varying the age-stratified vaccine allocation to find the minimum herd immunity requirements (the effective reproduction number Reff<1 with closed borders) under various vaccine effectiveness (VE) scenarios and R0 values. We ran two-year open-border simulations for two vaccine strategies: minimising Reff and targeting high-risk groups. Findings: Targeting of high-risk groups will result in lower hospitalisations and deaths in most scenarios. Reaching the herd immunity threshold (HIT) with a vaccine of 90% VE against disease and 80% VE against infection requires at least 86•5% total population uptake for R0=4•5 (with high vaccination coverage for 30-49-year-olds) and 98•1% uptake for R0=6. In a two-year open-border scenario with 10 overseas cases daily and 90% total population vaccine uptake (including 0-15 year olds) with the same vaccine, the strategy of targeting high-risk groups is close to achieving HIT, with an estimated 11,400 total hospitalisations (peak 324 active and 36 new daily cases in hospitals), and 1,030 total deaths. Interpretation: Targeting high-risk groups for vaccination will result in fewer hospitalisations and deaths with open borders compared to targeting reduced transmission. With a highly effective vaccine and a high total uptake, opening borders will result in increasing cases, hospitalisations, and deaths. Other public health and social measures will still be required as part of an effective pandemic response. Funding: This project was funded by the Health Research Council [20/1018]. Research in context.
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.
Pangenome graphs in infectious disease: a comprehensive genetic variation analysis of Neisseria meningitidis leveraging Oxford Nanopore long reads.
(Frontiers Media S.A., 2023-08-10) Yang Z; Guarracino A; Biggs PJ; Black MA; Ismail N; Wold JR; Merriman TR; Prins P; Garrison E; de Ligt J; Hane J
Whole genome sequencing has revolutionized infectious disease surveillance for tracking and monitoring the spread and evolution of pathogens. However, using a linear reference genome for genomic analyses may introduce biases, especially when studies are conducted on highly variable bacterial genomes of the same species. Pangenome graphs provide an efficient model for representing and analyzing multiple genomes and their variants as a graph structure that includes all types of variations. In this study, we present a practical bioinformatics pipeline that employs the PanGenome Graph Builder and the Variation Graph toolkit to build pangenomes from assembled genomes, align whole genome sequencing data and call variants against a graph reference. The pangenome graph enables the identification of structural variants, rearrangements, and small variants (e.g., single nucleotide polymorphisms and insertions/deletions) simultaneously. We demonstrate that using a pangenome graph, instead of a single linear reference genome, improves mapping rates and variant calling for both simulated and real datasets of the pathogen Neisseria meningitidis. Overall, pangenome graphs offer a promising approach for comparative genomics and comprehensive genetic variation analysis in infectious disease. Moreover, this innovative pipeline, leveraging pangenome graphs, can bridge variant analysis, genome assembly, population genetics, and evolutionary biology, expanding the reach of genomic understanding and applications.
Spatial and temporal transmission dynamics of respiratory syncytial virus in New Zealand before and after the COVID-19 pandemic.
(Cold Spring Harbor Laboratory, 2024-07-17) Jelley L; Douglas J; O'Neill M; Berquist K; Claasen A; Wang J; Utekar S; Johnston H; Bocacao J; Allais M; de Ligt J; Ee Tan C; Seeds R; Wood T; Aminisani N; Jennings T; Welch D; Turner N; McIntyre P; Dowell T; Trenholme A; Byrnes C; SHIVERS investigation team; Webby R; French N; Winter D; Huang QS; Geoghegan JL
Human respiratory syncytial virus (RSV) is a major cause of acute respiratory infection. In 2020, RSV was effectively eliminated from the community in New Zealand due to non-pharmaceutical interventions (NPI) used to control the spread of COVID-19. However, in April 2021, following a brief quarantine-free travel agreement with Australia, there was a large-scale nationwide outbreak of RSV that led to reported cases more than five times higher, and hospitalisations more than three times higher, than the typical seasonal pattern. In this study, we generated 1,471 viral genomes of both RSV-A and RSV-B sampled between 2015 and 2022 from across New Zealand. Using a phylodynamics approach, we used these data to better understand RSV transmission patterns in New Zealand prior to 2020, and how RSV became re-established in the community following the relaxation of COVID-19 restrictions. We found that in 2021, there was a large epidemic of RSV in New Zealand that affected a broader age group range compared to the usual pattern of RSV infections. This epidemic was due to an increase in RSV importations, leading to several large genomic clusters of both RSV-A ON1 and RSV-B BA9 genotypes in New Zealand. However, while a number of importations were detected, there was also a major reduction in RSV genetic diversity compared to pre-pandemic seasonal outbreaks. These genomic clusters were temporally associated with the increase of migration in 2021 due to quarantine-free travel from Australia at the time. The closest genetic relatives to the New Zealand RSV genomes, when sampled, were viral genomes sampled in Australia during a large, off-season summer outbreak several months prior, rather than cryptic lineages that were sustained but not detected in New Zealand. These data reveal the impact of NPI used during the COVID-19 pandemic on other respiratory infections and highlight the important insights that can be gained from viral genomes.
Temporal reconstruction of a Salmonella Enteritidis ST11 outbreak in New Zealand
(Microbiology Society, 2025-10-30) Strydom H; Wright J; Bromhead C; Welch D; Williams E; Mulqueen K; de Ligt J; Biggs PJ; Paine S; Jefferies S; French N
Outbreaks caused by Salmonella Enteritidis are commonly linked to eggs and poultry meat internationally, but this serovar had never been detected in Aotearoa New Zealand (NZ) poultry prior to 2021. Locally designated genomic cluster Salmonella Enteritidis_2019_C_01, was implicated in a 2019 outbreak associated with a restaurant in Auckland. Four Enteritidis_2019_C_01 sub-clusters have since been identified, two retrospectively, in the Auckland region. Authorities initiated a formal outbreak investigation after genomically indistinguishable S. Enteritidis was isolated from the NZ poultry production environment. This study analysed 231 S. Enteritidis genomes obtained from the outbreak using Bayesian phylodynamic tools to gain insight into the outbreak's dynamics and origin. We used Bayesian integrated coalescent epoch plots to estimate the change of the Enteritidis ST11 population size over time and marginal structured coalescent approximation to estimate transmission between poultry producers. We investigated human and poultry isolates to elucidate the time and location of the most recent common ancestor of the outbreak and transmission pathways. The median most recent common ancestor was estimated to be February 2019. We found evidence of amplification and spread of strain Enteritidis_2019_C_01 within the poultry industry, as well as transmission events throughout the production chain. The intervention by the public health and food safety authorities coincided with a drop in the effective population size of the S. Enteritidis ST11 as well as notified human cases. This information is crucial for understanding and preventing the transmission of S. Enteritidis in NZ poultry to ensure poultry meat and eggs are safe for consumption.
Tracing the international arrivals of SARS-CoV-2 Omicron variants after Aotearoa New Zealand reopened its border
(Springer Nature Limited, 2022-10-29) Douglas J; Winter D; McNeill A; Carr S; Bunce M; French N; Hadfield J; de Ligt J; Welch D; Geoghegan JL
In the second quarter of 2022, there was a global surge of emergent SARS-CoV-2 lineages that had a distinct growth advantage over then-dominant Omicron BA.1 and BA.2 lineages. By generating 10,403 Omicron genomes, we show that Aotearoa New Zealand observed an influx of these immune-evasive variants (BA.2.12.1, BA.4, and BA.5) through the border. This is explained by the return to significant levels of international travel following the border's reopening in March 2022. We estimate one Omicron transmission event from the border to the community for every ~5,000 passenger arrivals at the current levels of travel and restriction. Although most of these introductions did not instigate any detected onward transmission, a small minority triggered large outbreaks. Genomic surveillance at the border provides a lens on the rate at which new variants might gain a foothold and trigger new waves of infection.
Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch
(F1000 Research Limited, 2021-09-17) O'Toole Á; Hill V; Pybus OG; Watts A; Bogoch II; Khan K; Messina JP; COVID-19 Genomics UK (COG-UK) consortium; Network for Genomic Surveillance in South Africa (NGS-SA); Brazil-UK CADDE Genomic Network; Tegally H; Lessells RR; Giandhari J; Pillay S; Tumedi KA; Nyepetsi G; Kebabonye M; Matsheka M; Mine M; Tokajian S; Hassan H; Salloum T; Merhi G; Koweyes J; Geoghegan JL; de Ligt J; Ren X; Storey M; Freed NE; Pattabiraman C; Prasad P; Desai AS; Vasanthapuram R; Schulz TF; Steinbrück L; Stadler T; Swiss Viollier Sequencing Consortium; Parisi A; Bianco A; García de Viedma D; Buenestado-Serrano S; Borges V; Isidro J; Duarte S; Gomes JP; Zuckerman NS; Mandelboim M; Mor O; Seemann T; Arnott A; Draper J; Gall M; Rawlinson W; Deveson I; Schlebusch S; McMahon J; Leong L; Lim CK; Chironna M; Loconsole D; Bal A; Josset L; Holmes E; St George K; Lasek-Nesselquist E; Sikkema RS; Oude Munnink B; Koopmans M; Brytting M; Sudha Rani V; Pavani S; Smura T; Heim A; Kurkela S; Umair M; Salman M; Bartolini B; Rueca M; Drosten C; Wolff T; Silander O; Eggink D; Reusken C; Vennema H; Park A; Carrington C; Sahadeo N; Carr M; Gonzalez G; SEARCH Alliance San Diego; National Virus Reference Laboratory; SeqCOVID-Spain; Danish Covid-19 Genome Consortium (DCGC); Communicable Diseases Genomic Network (CDGN); Dutch National SARS-CoV-2 surveillance program; Division of Emerging Infectious Diseases (KDCA); de Oliveira T; Faria N; Rambaut A; Kraemer MUG
Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.