Journal Articles
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Item 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 KCampylobacter 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.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 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 MDCampylobacter 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.Item 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 NDisentangling 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.Item Dientamoeba fragilis associated with microbiome diversity changes in acute gastroenteritis patients.(Elsevier B.V., 2023-12-01) Muhsin-Sharafaldine M-R; Abdel Rahman L; Suwanarusk R; Grant J; Parslow G; French N; Tan KSW; Russell B; Morgan XC; Ussher JEThis study examined the correlation between intestinal protozoans and the bacterial microbiome in faecal samples collected from 463 patients in New Zealand who were diagnosed with gastroenteritis. In comparison to traditional microscopic diagnosis methods, Multiplexed-tandem PCR proved to be more effective in detecting intestinal parasites. Among the identified protozoans, Blastocystis sp. and Dientamoeba fragilis were the most prevalent. Notably, D. fragilis was significantly associated with an increase in the alpha-diversity of host prokaryotic microbes. Although the exact role of Blastocystis sp. and D. fragilis as the primary cause of gastroenteritis remains debatable, our data indicates a substantial correlation between these protozoans and the prokaryote microbiome of their hosts, particularly when compared to other protists or patients with gastroenteritis but no detectable parasitic cause. These findings underscore the significance of comprehending the contributions of intestinal protozoans, specifically D. fragilis, to the development of gastroenteritis and their potential implications for disease management.Item Prevalence and Load of the Campylobacter Genus in Infants and Associated Household Contacts in Rural Eastern Ethiopia: a Longitudinal Study from the Campylobacter Genomics and Environmental Enteric Dysfunction (CAGED) Project(American Society for Microbiology, 2023-07-26) Deblais L; Ojeda A; Brhane M; Mummed B; Hassen KA; Ahmedo BU; Weldesenbet YD; Amin JK; Ahmed IA; Usmane IA; Yusuf EA; Seran AJ; Abrahim FI; Game HT; Mummed BA; Usmail MM; Umer KA; Dawid MM; Gebreyes W; French N; Hassen JY; Roba KT; Mohammed A; Yimer G; Saleem C; Chen D; Singh N; Manary MJ; McKune SL; Havelaar AH; Rajashekara G; Elkins CAIn our previous cross-sectional study, multiple species of Campylobacter were detected (88%) in stool samples from children (12 to 14 months of age) in rural eastern Ethiopia. This study assessed the temporal fecal carriage of Campylobacter in infants and identified putative reservoirs associated with these infections in infants from the same region. The prevalence and load of Campylobacter were determined using genus-specific real-time PCR. Stool samples from 106 infants (n = 1,073) were collected monthly from birth until 376 days of age (DOA). Human stool samples (mothers and siblings), livestock feces (cattle, chickens, goats, and sheep), and environmental samples (soil and drinking water) from the 106 households were collected twice per household (n = 1,644). Campylobacter was most prevalent in livestock feces (goats, 99%; sheep, 98%; cattle, 99%; chickens, 93%), followed by human stool samples (siblings, 91%; mothers, 83%; infants, 64%) and environmental samples (soil, 58%; drinking water, 43%). The prevalence of Campylobacter in infant stool samples significantly increased with age, from 30% at 27 DOA to 89% at 360 DOA (1% increase/day in the odds of being colonized) (P < 0.001). The Campylobacter load increased linearly (P < 0.001) with age from 2.95 logs at 25 DOA to 4.13 logs at 360 DOA. Within a household, the Campylobacter load in infant stool samples was positively correlated with the load in mother stool samples (r2 = 0.18) and soil collected inside the house (r2 = 0.36), which were in turn both correlated with Campylobacter loads in chicken and cattle feces (0.60 < r2 < 0.63) (P < 0.01). In conclusion, a high proportion of infants are infected with Campylobacter in eastern Ethiopia, and contact with the mother and contaminated soil may be associated with early infections. IMPORTANCE A high Campylobacter prevalence during early childhood has been associated with environmental enteric dysfunction (EED) and stunting, especially in low-resource settings. Our previous study demonstrated that Campylobacter was frequently found (88%) in children from eastern Ethiopia; however, little is known about potential Campylobacter reservoirs and transmission pathways leading to infection of infants by Campylobacter during early growth. In the longitudinal study presented here, Campylobacter was frequently detected in infants within the 106 surveyed households from eastern Ethiopia, and the prevalence was age dependent. Furthermore, preliminary analyses highlighted the potential role of the mother, soil, and livestock in the transmission of Campylobacter to the infant. Further work will explore the species and genetic composition of Campylobacter in infants and putative reservoirs using PCR and whole-genome and metagenomic sequencing. The findings from these studies can lead to the development of interventions to minimize the risk of transmission of Campylobacter to infants and, potentially, EED and stunting.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 Unravelling the reservoirs for colonisation of infants with Campylobacter spp. in rural Ethiopia: protocol for a longitudinal study during a global pandemic and political tensions.(BMJ Publishing Group Ltd, 2022-10-05) Havelaar AH; Brhane M; Ahmed IA; Kedir J; Chen D; Deblais L; French N; Gebreyes WA; Hassen JY; Li X; Manary MJ; Mekuria Z; Ibrahim AM; Mummed B; Ojeda A; Rajashekara G; Roba KT; Saleem C; Singh N; Usmane IA; Yang Y; Yimer G; McKune SINTRODUCTION: Undernutrition is an underlying cause of mortality in children under five (CU5) years of age. Animal-source foods have been shown to decrease malnutrition in CU5. Livestock are important reservoirs for Campylobacter bacteria, which are recognised as risk factors for child malnutrition. Increasing livestock production may be beneficial for improving nutrition of children but these benefits may be negated by increased exposure to Campylobacter and research is needed to evaluate the complex pathways of Campylobacter exposure and infection applicable to low-income and middle-income countries. We aim to identify reservoirs of infection with Campylobacter spp. of infants in rural Eastern Ethiopia and evaluate interactions with child health (environmental enteric dysfunction and stunting) in the context of their sociodemographic environment. METHODS AND ANALYSIS: This longitudinal study involves 115 infants who are followed from birth to 12 months of age and are selected randomly from 10 kebeles of Haramaya woreda, East Hararghe zone, Oromia region, Ethiopia. Questionnaire-based information is obtained on demographics, livelihoods, wealth, health, nutrition and women empowerment; animal ownership/management and diseases; and water, sanitation and hygiene. Faecal samples are collected from infants, mothers, siblings and livestock, drinking water and soil. These samples are analysed by a range of phenotypic and genotypic microbiological methods to characterise the genetic structure of the Campylobacter population in each of these reservoirs, which will support inference about the main sources of exposure for infants. ETHICS AND DISSEMINATION: Ethical approval was obtained from the University of Florida Internal Review Board (IRB201903141), the Haramaya University Institutional Health Research Ethics Committee (COHMS/1010/3796/20) and the Ethiopia National Research Ethics Review Committee (SM/14.1/1059/20). Written informed consent is obtained from all participating households. Research findings will be disseminated to stakeholders through conferences and peer-reviewed journals and through the Feed the Future Innovation Lab for Livestock Systems.