Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item 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 NOutbreaks 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.Item 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 JLHuman 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.Item Severe weather events and cryptosporidiosis in Aotearoa New Zealand: A case series of space-time clusters.(Cambridge University Press, 2024-04-15) Grout L; Hales S; Baker MG; French N; Wilson NOccurrence of cryptosporidiosis has been associated with weather conditions in many settings internationally. We explored statistical clusters of human cryptosporidiosis and their relationship with severe weather events in New Zealand (NZ). Notified cases of cryptosporidiosis from 1997 to 2015 were obtained from the national surveillance system. Retrospective space-time permutation was used to identify statistical clusters. Cluster data were compared to severe weather events in a national database. SaTScan analysis detected 38 statistically significant cryptosporidiosis clusters. Around a third (34.2%, 13/38) of these clusters showed temporal and spatial alignment with severe weather events. Of these, nearly half (46.2%, 6/13) occurred in the spring. Only five (38%, 5/13) of these clusters corresponded to a previously reported cryptosporidiosis outbreak. This study provides additional evidence that severe weather events may contribute to the development of some cryptosporidiosis clusters. Further research on this association is needed as rainfall intensity is projected to rise in NZ due to climate change. The findings also provide further arguments for upgrading the quality of drinking water sources to minimize contamination with pathogens from runoff from livestock agriculture.Item Creating symptom-based criteria for diagnostic testing: a case study based on a multivariate analysis of data collected during the first wave of the COVID-19 pandemic in New Zealand(BioMed Central Ltd, 2021-12) French N; Jones G; Heuer C; Hope V; Jefferies S; Muellner P; McNeill A; Haslett S; Priest PBACKGROUND: Diagnostic testing using PCR is a fundamental component of COVID-19 pandemic control. Criteria for determining who should be tested by PCR vary between countries, and ultimately depend on resource constraints and public health objectives. Decisions are often based on sets of symptoms in individuals presenting to health services, as well as demographic variables, such as age, and travel history. The objective of this study was to determine the sensitivity and specificity of sets of symptoms used for triaging individuals for confirmatory testing, with the aim of optimising public health decision making under different scenarios. METHODS: Data from the first wave of COVID-19 in New Zealand were analysed; comprising 1153 PCR-confirmed and 4750 symptomatic PCR negative individuals. Data were analysed using Multiple Correspondence Analysis (MCA), automated search algorithms, Bayesian Latent Class Analysis, Decision Tree Analysis and Random Forest (RF) machine learning. RESULTS: Clinical criteria used to guide who should be tested by PCR were based on a set of mostly respiratory symptoms: a new or worsening cough, sore throat, shortness of breath, coryza, anosmia, with or without fever. This set has relatively high sensitivity (> 90%) but low specificity (< 10%), using PCR as a quasi-gold standard. In contrast, a group of mostly non-respiratory symptoms, including weakness, muscle pain, joint pain, headache, anosmia and ageusia, explained more variance in the MCA and were associated with higher specificity, at the cost of reduced sensitivity. Using RF models, the incorporation of 15 common symptoms, age, sex and prioritised ethnicity provided algorithms that were both sensitive and specific (> 85% for both) for predicting PCR outcomes. CONCLUSIONS: If predominantly respiratory symptoms are used for test-triaging, a large proportion of the individuals being tested may not have COVID-19. This could overwhelm testing capacity and hinder attempts to trace and eliminate infection. Specificity can be increased using alternative rules based on sets of symptoms informed by multivariate analysis and automated search algorithms, albeit at the cost of sensitivity. Both sensitivity and specificity can be improved through machine learning algorithms, incorporating symptom and demographic data, and hence may provide an alternative approach to test-triaging that can be optimised according to prevailing conditions.Item 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 JLIn 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.Item 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 JLNew 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.Item Whole-genome sequencing and ad hoc shared genome analysis of Staphylococcus aureus isolates from a New Zealand primary school(Springer Nature Limited, 2021-10-13) Scott P; Zhang J; Anderson T; Priest PC; Chambers S; Smith H; Murdoch DR; French N; Biggs PJEpidemiological studies of communicable diseases increasingly use large whole-genome sequencing (WGS) datasets to explore the transmission of pathogens. It is important to obtain an initial overview of datasets and identify closely related isolates, but this can be challenging with large numbers of isolates and imperfect sequencing. We used an ad hoc whole-genome multi locus sequence typing method to summarise data from a longitudinal study of Staphylococcus aureus in a primary school in New Zealand. Each pair of isolates was compared and the number of genes where alleles differed between isolates was tallied to produce a matrix of "allelic differences". We plotted histograms of the number of allelic differences between isolates for: all isolate pairs; pairs of isolates from different individuals; and pairs of isolates from the same individual. 340 sequenced isolates were included, and the ad hoc shared genome contained 445 genes. There were between 0 and 420 allelic differences between isolate pairs and the majority of pairs had more than 260 allelic differences. We found many genetically closely related S. aureus isolates from single individuals and a smaller number of closely-related isolates from separate individuals. Multiple S. aureus isolates from the same individual were usually very closely related or identical over the ad hoc shared genome. Siblings carried genetically similar, but not identical isolates. An ad hoc shared genome approach to WGS analysis can accommodate imperfect sequencing of the included isolates, and can provide insights into relationships between isolates in epidemiological studies with large WGS datasets containing diverse isolates.Item Dairy Cattle Density and Temporal Patterns of Human Campylobacteriosis and Cryptosporidiosis in New Zealand(Springer Nature Switzerland AG on behalf of the EcoHealth Alliance, 2022-06-10) Grout L; Marshall J; Hales S; Baker MG; French NPublic health risks associated with the intensification of dairy farming are an emerging concern. Dairy cattle are a reservoir for a number of pathogens that can cause human illness. This study examined the spatial distribution of dairy cattle density and explored temporal patterns of human campylobacteriosis and cryptosporidiosis notifications in New Zealand from 1997 to 2015. Maps of dairy cattle density were produced, and temporal patterns of disease rates were assessed for urban versus rural areas and for areas with different dairy cattle densities using descriptive temporal analyses. Campylobacteriosis and cryptosporidiosis rates displayed strong seasonal patterns, with highest rates in spring in rural areas and, for campylobacteriosis, summer in urban areas. Increases in rural cases often preceded increases in urban cases. Furthermore, disease rates in areas with higher dairy cattle densities tended to peak before areas with low densities or no dairy cattle. Infected dairy calves may be a direct or indirect source of campylobacteriosis or cryptosporidiosis infection in humans through environmental or occupational exposure routes, including contact with animals or feces, recreational contact with contaminated waterways, and consumption of untreated drinking water. These results have public health implications for populations living, working, or recreating in proximity to dairy farms.Item Stigmatising and Racialising COVID-19: Asian People’s Experience in New Zealand(Springer Nature, 2022-11-11) Liu LS; Jia X; Zhu A; Ran GJ; Siegert R; French N; Johnston DThe Asian community — the second largest non-European ethnic community in New Zealand — plays an important role in combatting the COVID-19 pandemic, evidenced by their active advocation for border control and mass masking. Despite the long history of racial discrimination against the Asian population, the Asian community has experienced certain degrees of racial discrimination associated with the stigmatisation as the cause of the COVID-19 outbreak in New Zealand. Based on data from a quantitative online survey with 402 valid responses within the Asian communities across New Zealand and the in-depth interviews with 19 Asian people in Auckland, New Zealand, this paper will illustrate Asian people’s experience of racial discrimination and stigmatisation during the pandemic in the country. The survey shows that since the outbreak of COVID-19, under a quarter of the participants reported experiencing discrimination, and a third reported knowing an immediate contact who had experienced discrimination. However, when looking beyond their immediate social circle, an even higher proportion reported noticing racism and stigmatisation through the traditional or social media due to COVID-19. Major variations of the degree of racial discrimination experienced are determined by three demographic variables: ethnicity, age, and region. The in-depth interviews largely echoed the survey findings and highlighted a strong correlation between the perceived racial discrimination among the local Asian community and the stigmatisation associated with COVID-19. These findings are important for improving the way we manage future pandemics and other disasters within the context of the UN Sendai Framework for Disaster Risk Reduction.