Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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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.
Longitudinal survey investigating vectors and reservoirs for Campylobacter colonization of chickens on a New Zealand broiler poultry farm
(American Society for Microbiology, 2025-09-17) Kingsbury JM; French N; Midwinter A; Lucas R; Callander M; Hird CP; Smith S; Mulqueen K; Biggs R; Biggs PJ; Ercolini D
This longitudinal survey followed the life cycle of a New Zealand broiler flock to investigate sources of flock colonization by Campylobacter. Samples were collected at frequent intervals from potential Campylobacter reservoirs and sources, transmission routes for Campylobacter ingress into the broiler shed, and to monitor flock colonization. Of the 738 samples, 200 (27%) tested positive for Campylobacter. Campylobacter species from sample isolates included 316 Campylobacter jejuni, 39 Campylobacter coli, and 8 Campylobacter lari isolates; only C. jejuni was isolated from chickens. C. jejuni isolates (n = 199) were sequenced and consisted of seven sequence types (STs); the most abundant was ST6964 (105 isolates). Most flock isolates were ST6964 (44 isolates) or ST50 (27 isolates). ST6964 isolates closely matched those from the previous flock and another age-matched flock on the same farm, supporting a role for an on-farm reservoir contaminating flocks. There were six STs from catching crew and equipment isolates; the most prevalent were ST6964 (19 isolates) and ST50 (21 isolates). The close genetic match, high Campylobacter prevalence in catching samples (59/130, 45%), and the timing of flock colonization occurring closely following catcher presence in the shed support that catchers and equipment might also contaminate the shed and flock from prior flocks that they visited. There was no evidence for wildlife, feed, drinking water, breeder flock, or shed litter as sources of the Campylobacter genotypes colonizing the flock. Taken together, this study identified key areas where the poultry industry might focus on-farm risk management practices to reduce colonization of broiler flocks by Campylobacter.IMPORTANCECampylobacteriosis is the most frequently notified enteric disease in New Zealand, and New Zealand has one of the highest rates of campylobacteriosis among industrialized countries. Reducing Campylobacter colonization of poultry at the farm level would reduce reliance on processing interventions for reducing Campylobacter contamination of broiler meat. This study aimed to identify on-farm sources of Campylobacter contamination in New Zealand broiler chicken flocks. No evidence was found that wildlife, chicken feed, drinking water, or parent breeder flocks were contaminating sources. Instead, carryover of Campylobacter from the previous flock or other farm flocks, and/or contamination from chicken catching crews and their equipment, may have contributed Campylobacter strains that colonized the study flock. These are key areas where the poultry industry might focus on-farm risk management practices to reduce colonization of broiler flocks by Campylobacter.
Genomic analysis of the 2017 Aotearoa New Zealand outbreak of Mycoplasma bovis and its position within the global population structure
(Frontiers Media S.A., 2025-07-23) Binney BM; Gias E; Foxwell J; Little A; Biggs PJ; French N; Lambert CL; Ha HJ; Carter GP; Gyuranecz M; Pardon B; De Vliegher S; Boyen F; Bokma J; Krömker V; Wente N; Mahony TJ; Gibson JS; Barnes TS; Wawegama N; Legione AR; Heller M; Schnee C; Pelkonen S; Autio T; Higuchi H; Gondaira S; McCulley M; Cloeckaert A
In 2017 an outbreak of Mycoplasma bovis (M. bovis), an infectious agent of cattle, was identified in Aotearoa New Zealand. This study characterizes the genomic population structure of the outbreak in New Zealand and compares it with the known global population structure using multilocus sequence typing (MLST) and genomic analysis. The New Zealand outbreak strain was MLST genotyped as ST21. A comprehensive collection of 840 genomes from the New Zealand outbreak showed a pattern of clonal expansion when characterized by MLST, core genome MLST (cgMLST) and whole genome MLST (wgMLST). A lineage of genomes was found with no in silico identifiable pta2 locus, a housekeeping gene used in the MLST scheme. We compared a sample set of 40 New Zealand genomes to 47 genomes from other countries. This group had 79 ST21 genomes and eight genomes that were single nucleotide polymorphism (SNP) variants within the MLST loci of ST21. Two of the 47 international genomes showed signs of extensive unique recombination. Unique alleles in six genes were identified as present only in the New Zealand genomes. These novel variants were in the genes; haeIIIM encoding for cytosine-specific methyltransferase, cysC encoding for cysteinyl tRNA synthetase, era encoding for GTPase Era, metK encoding for S-adenosylmethionine synthase, parE encoding for DNA topoisomerase, and hisS encoding for histidine-tRNA ligase. This finding could be due to a population bottleneck, genetic drift, or positive selection. The same sample set of 40 New Zealand genomes were compared using MLST to 404 genomes from 15 other countries and 11 genomes without a known country. A FastBAPS analysis of 455 genomes showed a global population structure with 11 clusters. Some countries, such as Canada, Denmark and Australia contained both internally closely related genomes and some genomes that were more closely related to genomes found in other countries. Our results support the need for Whole Genome Sequencing (WGS) as well as MLST genotyping in M. bovis outbreaks. They also support the importance of understanding the national and international movement patterns of cattle and their genetic material, as possible routes of transmission, when managing the spread of M. bovis.
Practitioner perspectives on informing decisions in One Health sectors with predictive models
(Springer Nature Limited, 2025-12-01) Pepin KM; Carlisle K; Chipman RB; Cole D; Anderson DP; Baker MG; Benschop J; Bunce M; Binny RN; French N; Greenhalgh S; O’Neale DRJ; McDougall S; Morgan FJ; Muellner P; Murphy E; Plank MJ; Tompkins DM; Hayman DTS
The continued emergence of challenges in human, animal, and environmental health (One Health sectors) requires public servants to make management and policy decisions about system-level ecological and sociological processes that are complex, poorly understood, and change over time. Relying on intuition, evidence, and experience for robust decision-making is challenging without a formal assimilation of these elements (a model), especially when the decision needs to consider potential impacts if an action is or is not taken. Models can provide assistance to this challenge, but effective development and use of model-based evidence in decision-making (‘model-to-decision workflow’) can be challenging. To address this gap, we examined conditions that maximize the value of model-based evidence in decision-making in One Health sectors by conducting 41 semi-structured interviews of researchers, science advisors, operational managers, and policy decision-makers with direct experience in model-to-decision workflows (‘Practitioners’) in One Health sectors. Broadly, our interview guide was structured to understand practitioner perspectives about the utility of models in health policy or management decision-making, challenges and risks with using models in this capacity, experience with using models, factors that affect trust in model-based evidence, and perspectives about conditions that lead to the most effective model-to-decision workflow. We used inductive qualitative analysis of the interview data with iterative coding to identify key themes for maximizing the value of model-based evidence in One Health applications. Our analysis describes practitioner perspectives for improved collaboration among modelers and decision-makers in public service, and priorities for increasing accessibility and value of model-based evidence in One Health decision-making. Two emergent priorities include establishing different standards for development of model-based evidence before or after decisions are made, or in real-time versus preparedness phases of emergency response, and investment in knowledge brokers with modeling expertise working in teams with decision-makers.
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.
Ethnic equity in Aotearoa New Zealand's COVID-19 response: A descriptive epidemiological study
(Elsevier Limited, United Kingdom, on behalf of The Royal Society for Public Health, 2025-07) Jefferies S; Gilkison C; Duff P; Grey C; French N; Carr H; Priest P; Crengle S
Objectives: Aotearoa New Zealand employed one of the most stringent public health pandemic responses internationally. We investigated whether ethnic health equity was achieved in the response and outcomes, from COVID-19 elimination in June 2020 through to Omicron-response easing, including international border reopening, in 2022. Study design: Descriptive epidemiology study. Methods: All COVID-19 cases, patients tested for SARS-CoV-2 and people vaccinated against COVID-19 between 9 June 2020 and 13 April 2022 were examined over three response periods: by demographic features and COVID-19 outcomes, transmission and vaccination patterns, time-to-vaccination and testing rates. Results: There were 15,693 cases per 100,000, 138·7 hospitalisations per 100,000, and 9·8 deaths per 100,000 people. Pacific peoples and Indigenous Māori had, respectively, 9·3 to 35-fold and 1·5 to 8·3-fold higher risk of COVID-19, 5·1-fold and 2·6-fold higher age-standardised risk of hospitalisation and 9-fold and 4-fold higher age-standardised risk of death, than European or Other. Māori and Pacific peoples had lower vaccination coverage at critical points in the response, and slower access to vaccination (Adjusted Time Ratios for two doses 1·32 (95% CI 1·31–1·32) and 1·14 (1·14–1·14), respectively), than European or Other. Testing rates remained high, especially among Māori and Pacific peoples. Conclusions: Despite achieving a low overall burden of disease by international comparisons, the multi-faceted New Zealand response did not prevent stark ethnic inequities in access to vaccination and COVID-19 outcomes. Policies which address disparities in upstream determinants, early vaccine programme planning and implementation with high-risk communities, and prioritisation that addresses systematic ethnic disadvantage and promotes health equity in response decisions is recommended.
Source attribution of campylobacteriosis in Australia, 2017-2019.
(John Wiley and Sons, Inc., 2023-12-01) McLure A; Smith JJ; Firestone SM; Kirk MD; French N; Fearnley E; Wallace R; Valcanis M; Bulach D; Moffatt CRM; Selvey LA; Jennison A; Cribb DM; Glass K
Campylobacter jejuni and Campylobacter coli infections are the leading cause of foodborne gastroenteritis in high-income countries. Campylobacter colonizes a variety of warm-blooded hosts that are reservoirs for human campylobacteriosis. The proportions of Australian cases attributable to different animal reservoirs are unknown but can be estimated by comparing the frequency of different sequence types in cases and reservoirs. Campylobacter isolates were obtained from notified human cases and raw meat and offal from the major livestock in Australia between 2017 and 2019. Isolates were typed using multi-locus sequence genotyping. We used Bayesian source attribution models including the asymmetric island model, the modified Hald model, and their generalizations. Some models included an "unsampled" source to estimate the proportion of cases attributable to wild, feral, or domestic animal reservoirs not sampled in our study. Model fits were compared using the Watanabe-Akaike information criterion. We included 612 food and 710 human case isolates. The best fitting models attributed >80% of Campylobacter cases to chickens, with a greater proportion of C. coli (>84%) than C. jejuni (>77%). The best fitting model that included an unsampled source attributed 14% (95% credible interval [CrI]: 0.3%-32%) to the unsampled source and only 2% to ruminants (95% CrI: 0.3%-12%) and 2% to pigs (95% CrI: 0.2%-11%) The best fitting model that did not include an unsampled source attributed 12% to ruminants (95% CrI: 1.3%-33%) and 6% to pigs (95% CrI: 1.1%-19%). Chickens were the leading source of human Campylobacter infections in Australia in 2017-2019 and should remain the focus of interventions to reduce burden.
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 N
Occurrence 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.
Genomic and clinical characteristics of campylobacteriosis in Australia.
(Microbiology Society, 2024-01) Cribb DM; Moffatt CRM; Wallace RL; McLure AT; Bulach D; Jennison AV; French N; Valcanis M; Glass K; Kirk MD
Campylobacter spp. are a common cause of bacterial gastroenteritis in Australia, primarily acquired from contaminated meat. We investigated the relationship between genomic virulence characteristics and the severity of campylobacteriosis, hospitalisation, and other host factors.We recruited 571 campylobacteriosis cases from three Australian states and territories (2018-2019). We collected demographic, health status, risk factors, and self-reported disease data. We whole genome sequenced 422 C. jejuni and 84 C. coli case isolates along with 616 retail meat isolates. We classified case illness severity using a modified Vesikari scoring system, performed phylogenomic analysis, and explored risk factors for hospitalisation and illness severity.On average, cases experienced a 7.5 day diarrhoeal illness with additional symptoms including stomach cramps (87.1 %), fever (75.6 %), and nausea (72.0 %). Cases aged ≥75 years had milder symptoms, lower Vesikari scores, and higher odds of hospitalisation compared to younger cases. Chronic gastrointestinal illnesses also increased odds of hospitalisation. We observed significant diversity among isolates, with 65 C. jejuni and 21 C. coli sequence types. Antimicrobial resistance genes were detected in 20.4 % of isolates, but multidrug resistance was rare (0.04 %). Key virulence genes such as cdtABC (C. jejuni) and cadF were prevalent (>90 % presence) but did not correlate with disease severity or hospitalisation. However, certain genes (e.g. fliK, Cj1136, and Cj1138) appeared to distinguish human C. jejuni cases from food source isolates.Campylobacteriosis generally presents similarly across cases, though some are more severe. Genotypic virulence factors identified in the literature to-date do not predict disease severity but may differentiate human C. jejuni cases from food source isolates. Host factors like age and comorbidities have a greater influence on health outcomes than virulence factors.
A mathematical, classical stratification modeling approach to disentangling the impact of weather on infectious diseases: A case study using spatio-temporally disaggregated Campylobacter surveillance data for England and Wales.
(Public Library of Science (PLoS), 2024-01-18) Lo Iacono G; Cook AJC; Derks G; Fleming LE; French N; Gillingham EL; Gonzalez Villeta LC; Heaviside C; La Ragione RM; Leonardi G; Sarran CE; Vardoulakis S; Senyah F; van Vliet AHM; Nichols G; Vega N
Disentangling the impact of the weather on transmission of infectious diseases is crucial for health protection, preparedness and prevention. Because weather factors are co-incidental and partly correlated, we have used geography to separate out the impact of individual weather parameters on other seasonal variables using campylobacteriosis as a case study. Campylobacter infections are found worldwide and are the most common bacterial food-borne disease in developed countries, where they exhibit consistent but country specific seasonality. We developed a novel conditional incidence method, based on classical stratification, exploiting the long term, high-resolution, linkage of approximately one-million campylobacteriosis cases over 20 years in England and Wales with local meteorological datasets from diagnostic laboratory locations. The predicted incidence of campylobacteriosis increased by 1 case per million people for every 5° (Celsius) increase in temperature within the range of 8°-15°. Limited association was observed outside that range. There were strong associations with day-length. Cases tended to increase with relative humidity in the region of 75-80%, while the associations with rainfall and wind-speed were weaker. The approach is able to examine multiple factors and model how complex trends arise, e.g. the consistent steep increase in campylobacteriosis in England and Wales in May-June and its spatial variability. This transparent and straightforward approach leads to accurate predictions without relying on regression models and/or postulating specific parameterisations. A key output of the analysis is a thoroughly phenomenological description of the incidence of the disease conditional on specific local weather factors. The study can be crucially important to infer the elusive mechanism of transmission of campylobacteriosis; for instance, by simulating the conditional incidence for a postulated mechanism and compare it with the phenomenological patterns as benchmark. The findings challenge the assumption, commonly made in statistical models, that the transformed mean rate of infection for diseases like campylobacteriosis is a mere additive and combination of the environmental variables.

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