Campylobacteriosis contributes strongly to the disease burden of food-borne pathogens. Case-control studies are limited in attributing human infections to the different reservoirs because they can ...only trace back to the points of exposure, which may not point to the original reservoirs because of cross-contamination. Human Campylobacter infections can be attributed to specific reservoirs by estimating the extent of subtype sharing between strains from humans and reservoirs using multilocus sequence typing (MLST).
We investigated risk factors for human campylobacteriosis caused by Campylobacter strains attributed to different reservoirs. Sequence types (STs) were determined for 696 C. jejuni and 41 C. coli strains from endemic human cases included in a case-control study. The asymmetric island model, a population genetics approach for modeling Campylobacter evolution and transmission, attributed these cases to four putative animal reservoirs (chicken, cattle, sheep, pig) and to the environment (water, sand, wild birds) considered as a proxy for other unidentified reservoirs. Most cases were attributed to chicken (66%) and cattle (21%), identified as the main reservoirs in The Netherlands. Consuming chicken was a risk factor for campylobacteriosis caused by chicken-associated STs, whereas consuming beef and pork were protective. Risk factors for campylobacteriosis caused by ruminant-associated STs were contact with animals, barbecuing in non-urban areas, consumption of tripe, and never/seldom chicken consumption. Consuming game and swimming in a domestic swimming pool during springtime were risk factors for campylobacteriosis caused by environment-associated STs. Infections with chicken- and ruminant-associated STs were only partially explained by food-borne transmission; direct contact and environmental pathways were also important.
This is the first case-control study in which risk factors for campylobacteriosis are investigated in relation to the attributed reservoirs based on MLST profiles. Combining epidemiological and source attribution data improved campylobacteriosis risk factor identification and characterization, generated hypotheses, and showed that genotype-based source attribution is epidemiologically sensible.
In early 2020, during the COVID-19 pandemic, New Zealand implemented graduated, risk-informed national COVID-19 suppression measures aimed at disease elimination. We investigated their impacts on the ...epidemiology of the first wave of COVID-19 in the country and response performance measures.
We did a descriptive epidemiological study of all laboratory-confirmed and probable cases of COVID-19 and all patients tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in New Zealand from Feb 2 to May 13, 2020, after which time community transmission ceased. We extracted data from the national notifiable diseases database and the national SARS-CoV-2 test results repository. Demographic features and disease outcomes, transmission patterns (source of infection, outbreaks, household transmission), time-to-event intervals, and testing coverage were described over five phases of the response, capturing different levels of non-pharmaceutical interventions. Risk factors for severe outcomes (hospitalisation or death) were examined with multivariable logistic regression and time-to-event intervals were analysed by fitting parametric distributions using maximum likelihood estimation.
1503 cases were detected over the study period, including 95 (6·3%) hospital admissions and 22 (1·5%) COVID-19 deaths. The estimated case infection rate per million people per day peaked at 8·5 (95% CI 7·6–9·4) during the 10-day period of rapid response escalation, declining to 3·2 (2·8–3·7) in the start of lockdown and progressively thereafter. 1034 (69%) cases were imported or import related, tending to be younger adults, of European ethnicity, and of higher socioeconomic status. 702 (47%) cases were linked to 34 outbreaks. Severe outcomes were associated with locally acquired infection (crude odds ratio OR 2·32 95% CI 1·40–3·82 compared with imported), older age (adjusted OR ranging from 2·72 1·40–5·30 for 50–64 year olds to 8·25 2·59–26·31 for people aged ≥80 years compared with 20–34 year olds), aged residential care residency (adjusted OR 3·86 1·59–9·35), and Pacific peoples (adjusted OR 2·76 1·14–6·68) and Asian (2·15 1·10–4·20) ethnicities relative to European or other. Times from illness onset to notification and isolation progressively decreased and testing increased over the study period, with few disparities and increasing coverage of females, Māori, Pacific peoples, and lower socioeconomic groups.
New Zealand's response resulted in low relative burden of disease, low levels of population disease disparities, and the initial achievement of COVID-19 elimination.
Ministry of Business Innovation and Employment Strategic Scientific Investment Fund, and Ministry of Health, New Zealand.
Biuret deamination is an essential step in cyanuric acid mineralization. In the well-studied atrazine degrading bacterium Pseudomonas sp. strain ADP, the amidase AtzE catalyzes this step. However, ...Rhizobium leguminosarum bv. viciae 3841 uses an unrelated cysteine hydrolase, BiuH, instead. Herein, structures of BiuH, BiuH with bound inhibitor and variants of BiuH are reported. The substrate is bound in the active site by a hydrogen bonding network that imparts high substrate specificity. The structure of the inactive Cys175Ser BiuH variant with substrate bound in the active site revealed that an active site cysteine (Cys175), aspartic acid (Asp36) and lysine (Lys142) form a catalytic triad, which is consistent with biochemical studies of BiuH variants. Finally, molecular dynamics simulations highlighted the presence of three channels from the active site to the enzyme surface: a persistent tunnel gated by residues Val218 and Gln215 forming a potential substrate channel and two smaller channels formed by Val28 and a mobile loop (including residues Phe41, Tyr47 and Met51) that may serve as channels for co-product (ammonia) or co-substrate (water).
Extended-spectrum-beta-lactamase (ESBL)- or AmpC beta-lactamase (ACBL)-producing
bacteria are the most common cause of community-acquired multidrug-resistant urinary tract infections (UTIs) in New ...Zealand. The carriage of antimicrobial-resistant bacteria has been found in both people and pets from the same household; thus, the home environment may be a place where antimicrobial-resistant bacteria are shared between humans and pets. In this study, we sought to determine whether members (pets and people) of the households of human index cases with a UTI caused by an ESBL- or ACBL-producing
strain also carried an ESBL- or ACBL-producing
strain and, if so, whether it was a clonal match to the index case clinical strain. Index cases with a community-acquired UTI were recruited based on antimicrobial susceptibility testing of urine isolates. Fecal samples were collected from 18 non-index case people and 36 pets across 27 households. Eleven of the 27 households screened had non-index case household members (8/18 people and 5/36 animals) positive for ESBL- and/or ACBL-producing
strains. Whole-genome sequence analysis of 125
isolates (including the clinical urine isolates) from these 11 households showed that within seven households, the same strain of ESBL-/ACBL-producing
was cultured from both the index case and another person (5/11 households) or pet dog (2/11 households). These results suggest that transmission within the household may contribute to the community spread of ESBL- or ACBL-producing
that produce extended-spectrum beta-lactamases (ESBLs) and AmpC beta-lactamases (ACBLs) are important pathogens and can cause community-acquired illnesses, such as urinary tract infections (UTIs). Fecal carriage of these resistant bacteria by companion animals may pose a risk for transmission to humans. Our work evaluated the sharing of ESBL- and ACBL-producing
isolates between humans and companion animals. We found that in some households, dogs carried the same strain of ESBL-producing
as the household member with a UTI. This suggests that transmission events between humans and animals (or vice versa) are likely occurring within the home environment and, therefore, the community as a whole. This is significant from a health perspective, when considering measures to minimize community transmission, and highlights that in order to manage community spread, we need to consider interventions at the household level.
The number of microbes on Earth may be 10
, exceeding all other diversity. A small number of these can infect people and cause disease. The diversity of parasitic organisms likely correlates with the ...hosts they live in and the number mammal hosts for zoonotic infections increases with species richness among mammalian orders. Thus, while habitat loss and fragmentation may reduce species diversity, the habitat encroachment by people into species-rich areas may increase the exposure of people to novel infectious agents from wildlife. Here, we present a theoretical framework that exploits the species-area relationship to link the exposure of people to novel infections with habitat biodiversity. We model changes in human exposure to microbes through defined classes of habitat fragmentation and predict that increased habitat division intrinsically increases the hazard from microbes for all modelled biological systems. We apply our model to African tropical forests as an example. Our results suggest that it is possible to identify high-risk areas for the mitigation and surveillance of novel disease emergence and that mitigation measures may reduce this risk while conserving biodiversity.
•Pathogens were monitored in 16 New Zealand waterways supplying drinking water.•Cryptosporidium and Giardia were prevalent at sites with high numbers of ruminants.•Campylobacter and E. coli were ...prevalent in pasture catchments and after rain.•Catchment management is a vital tool for limiting outbreaks of waterborne disease.
Four microbes (Campylobacter spp., Escherichia coli, Cryptosporidium spp. and Giardia spp.) were monitored in 16 waterways that supply public drinking water for 13 New Zealand towns and cities. Over 500 samples were collected from the abstraction point at each study site every three months between 2009 and 2019. The waterways represent a range from small to large, free flowing to reservoir impoundments, draining catchments of entirely native vegetation to those dominated by pastoral agriculture. We used machine learning algorithms to explore the relative contribution of land use, catchment geology, vegetation, topography, and water quality characteristics of the catchment to determining the abundance and/or presence of each microbe. Sites on rivers draining predominantly agricultural catchments, the Waikato River, Oroua River and Waiorohi Stream had all four microbes present, often in high numbers, throughout the sampling interval. Other sites, such as the Hutt River and Big Huia Creek in Wellington which drain catchments of native vegetation, never had pathogenic microbes detected, or unsafe levels of E. coli. Boosted Regression Tree models could predict abundances and presence/absence of all four microbes with good precision using a wide range of potential environmental predictors covering land use, geology, vegetation, topography, and nutrient concentrations. Models were more accurate for protozoa than bacteria but did not differ markedly in their ability to predict abundance or presence/absence. Environmental drivers of microbe abundance or presence/absence also differed depending on whether the microbe was protozoan or bacterial. Protozoa were more prevalent in waterways with lower water quality, higher numbers of ruminants in the catchment, and in September and December. Bacteria were more abundant with higher rainfall, saturated soils, and catchments with greater than 35% of the land in agriculture. Although modern water treatment protocols will usually remove many pathogens from drinking water, several recent outbreaks of waterborne disease due to treatment failures, have highlighted the need to manage water supplies on multiple fronts. This research has identified potential catchment level variables, and thresholds, that could be better managed to reduce the potential for pathogens to enter drinking water supplies.
Campylobacteriosis in humans, caused by Campylobacter jejuni and Campylobacter coli, is the most common recognized bacterial zoonosis in the European Union and the United States. The acute phase is ...characterized by gastrointestinal symptoms. The long-term sequelae (Guillain-Barré syndrome, reactive arthritis, and postinfectious irritable bowel syndrome) contribute considerably to the disease burden. Attribution studies identified poultry as the reservoir responsible for up to 80% of the human Campylobacter infections. In the European Union, an estimated 30% of the human infections are associated with consumption and preparation of poultry meat. Until now, interventions in the poultry meat production chain have not been effectively introduced except for targeted interventions in Iceland and New Zealand. Intervention measures (eg, biosecurity) have limited effect or are hampered by economic aspects or consumer acceptance. In the future, a multilevel approach should be followed, aiming at reducing the level of contamination of consumer products rather than complete absence of Campylobacter.
Campylobacter and Salmonella, particularly non-typhoidal Salmonella, are important bacterial enteric pathogens of humans which are often carried asymptomatically in animal reservoirs. Bacterial ...foodborne infections, including those derived from meat, are associated with illness and death globally but the burden is disproportionately high in Africa. Commercial meat production is increasing and intensifying in many African countries, creating opportunities and threats for food safety.
Following Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, we searched six databases for English language studies published through June 2016, that reported Campylobacter or Salmonella carriage or infection prevalence in food animals and contamination prevalence in food animal products from African countries. A random effects meta-analysis and multivariable logistic regression were used to estimate the species-specific prevalence of Salmonella and Campylobacter and assess relationships between sample type and region and the detection or isolation of either pathogen.
Seventy-three studies reporting Campylobacter and 187 studies reporting Salmonella across 27 African countries were represented. Adjusted prevalence calculations estimate Campylobacter detection in 37.7% (95% CI 31.6–44.3) of 11,828 poultry samples; 24.6% (95% CI 18.0–32.7) of 1975 pig samples; 17.8% (95% CI 12.6–24.5) of 2907 goat samples; 12.6% (95% CI 8.4–18.5) of 2382 sheep samples; and 12.3% (95% CI 9.5–15.8) of 6545 cattle samples. Salmonella were detected in 13.9% (95% CI 11.7–16.4) of 25,430 poultry samples; 13.1% (95% CI 9.3–18.3) of 5467 pig samples; 9.3% (95% CI 7.2–12.1) of 2988 camel samples; 5.3% (95% CI 4.0–6.8) of 72,292 cattle samples; 4.8% (95% CI 3.6–6.3) of 11,335 sheep samples; and 3.4% (95% CI 2.2–5.2) of 4904 goat samples. ‘External’ samples (e.g. hide, feathers) were significantly more likely to be contaminated by both pathogens than ‘gut’ (e.g. faeces, cloaca) while meat and organs were significantly less likely to be contaminated than gut samples.
This study demonstrated widespread prevalence of Campylobacter species and Salmonella serovars in African food animals and meat, particularly in samples of poultry and pig origin. Source attribution studies could help ascertain which food animals are contributing to human campylobacteriosis and salmonellosis and direct potential food safety interventions.
•Campylobacter prevalence data was compiled from 14 African countries.•Salmonella prevalence data was compiled from 27 African countries.•Campylobacter and Salmonella were most prevalent in poultry and pig samples.•C. jejuni was the most predominant Campylobacter species except in pigs where C. coli predominates.•S. enterica serovar Typhimurium was the most commonly identified Salmonella serovar.
Although seasonality is a defining characteristic of many infectious diseases, few studies have described and compared seasonal patterns across diseases globally, impeding our understanding of ...putative mechanisms. Here, we review seasonal patterns across five enteric zoonotic diseases: campylobacteriosis, salmonellosis, vero-cytotoxigenic Escherichia coli (VTEC), cryptosporidiosis and giardiasis in the context of two primary drivers of seasonality: (i) environmental effects on pathogen occurrence and pathogen-host associations and (ii) population characteristics/behaviour.
We systematically reviewed published literature from 1960-2010, resulting in the review of 86 studies across the five diseases. The Gini coefficient compared temporal variations in incidence across diseases and the monthly seasonality index characterised timing of seasonal peaks. Consistent seasonal patterns across transnational boundaries, albeit with regional variations was observed. The bacterial diseases all had a distinct summer peak, with identical Gini values for campylobacteriosis and salmonellosis (0.22) and a higher index for VTEC (Gini 0.36). Cryptosporidiosis displayed a bi-modal peak with spring and summer highs and the most marked temporal variation (Gini = 0.39). Giardiasis showed a relatively small summer increase and was the least variable (Gini = 0.18).
Seasonal variation in enteric zoonotic diseases is ubiquitous, with regional variations highlighting complex environment-pathogen-host interactions. Results suggest that proximal environmental influences and host population dynamics, together with distal, longer-term climatic variability could have important direct and indirect consequences for future enteric disease risk. Additional understanding of the concerted influence of these factors on disease patterns may improve assessment and prediction of enteric disease burden in temperate, developed countries.
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