Antimicrobial resistance monitoring in the Danish swine production by phenotypic methods and metagenomics from 1999 to 2018.

BackgroundIn Denmark, antimicrobial resistance (AMR) in pigs has been monitored since 1995 by phenotypic approaches using the same indicator bacteria. Emerging methodologies, such as metagenomics, may allow novel surveillance ways.AimThis study aimed to assess the relevance of indicator bacteria (Escherichia coli and Enterococcus faecalis) for AMR surveillance in pigs, and the utility of metagenomics.MethodsWe collated existing data on AMR and antimicrobial use (AMU) from the Danish surveillance programme and performed metagenomics sequencing on caecal samples that had been collected/stored through the programme during 1999-2004 and 2015-2018. We compared phenotypic and metagenomics results regarding AMR, and the correlation of both with AMU.ResultsVia the relative abundance of AMR genes, metagenomics allowed to rank these genes as well as the AMRs they contributed to, by their level of occurrence. Across the two study periods, resistance to aminoglycosides, macrolides, tetracycline, and beta-lactams appeared prominent, while resistance to fosfomycin and quinolones appeared low. In 2015-2018 sulfonamide resistance shifted from a low occurrence category to an intermediate one. Resistance to glycopeptides consistently decreased during the entire study period. Outcomes of both phenotypic and metagenomics approaches appeared to positively correlate with AMU. Metagenomics further allowed to identify multiple time-lagged correlations between AMU and AMR, the most evident being that increased macrolide use in sow/piglets or fatteners led to increased macrolide resistance with a lag of 3-6 months.ConclusionWe validated the long-term usefulness of indicator bacteria and showed that metagenomics is a promising approach for AMR surveillance.

Practicalities of implementing burden of disease research in Africa: lessons from a population survey component of our multi-partner FOCAL research project.

BACKGROUND: Collaborative research is being increasingly implemented in Africa to study health-related issues, for example, the lack of evidence on disease burden, in particular for the presumptive high load of foodborne diseases. The FOCAL (Foodborne disease epidemiology, surveillance, and control in African LMIC) Project is a multi-partner study that includes a population survey to estimate the foodborne disease burden in four African low- and middle-income countries (LMICs). Our multi-partner study team had members from seven countries, all of whom contributed to the project from the grant application stage, and who play(ed) specific roles in designing and implementing the population survey. MAIN TEXT: In this paper, we applied Larkan et al.'s framework for successful research partnerships in global health to self-evaluate our project's collaboration, management, and implementation process. Our partnership formation considered the interplay and balance between operations and relations. Using Larkan et al.'s seven core concepts (i.e., focus, values, equity, benefit, communication, leadership, and resolution), we reviewed the process stated above in an African context. CONCLUSION: Through our current partnership and research implementing a population survey to study disease burden in four African LMICs, we observed that successful partnerships need to consider these core concepts explicitly, apply the essential leadership attributes, perform assessment of external contexts before designing the research, and expect differences in work culture. While some of these experiences are common to research projects in general, the other best practices and challenges we discussed can help inform future foodborne disease burden work in Africa.

Attribution of Illnesses Transmitted by Food and Water to Comprehensive Transmission Pathways Using Structured Expert Judgment, United States.

Illnesses transmitted by food and water cause a major disease burden in the United States despite advancements in food safety, water treatment, and sanitation. We report estimates from a structured expert judgment study using 48 experts who applied Cooke's classical model of the proportion of disease attributable to 5 major transmission pathways (foodborne, waterborne, person-to-person, animal contact, and environmental) and 6 subpathways (food handler-related, under foodborne; recreational, drinking, and nonrecreational/nondrinking, under waterborne; and presumed person-to-person-associated and presumed animal contact-associated, under environmental). Estimates for 33 pathogens were elicited, including bacteria such as Salmonella enterica, Campylobacter spp., Legionella spp., and Pseudomonas spp.; protozoa such as Acanthamoeba spp., Cyclospora cayetanensis, and Naegleria fowleri; and viruses such as norovirus, rotavirus, and hepatitis A virus. The results highlight the importance of multiple pathways in the transmission of the included pathogens and can be used to guide prioritization of public health interventions.

Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium.

Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to predict the animal reservoir from which a bacterial strain isolated from a human salmonellosis case originated based on whole-genome sequencing. Machine learning methods recognize patterns in large and complex data sets and use this knowledge to build models. The model learns patterns associated with genetic variations in bacteria isolated from the different animal reservoirs. We selected different machine learning algorithms to predict sources of human salmonellosis cases and trained the model with Danish Salmonella Typhimurium isolates sampled from broilers (n = 34), cattle (n = 2), ducks (n = 11), layers (n = 4), and pigs (n = 159). Using cgMLST as input features, the model yielded an average accuracy of 0.783 (95% CI: 0.77-0.80) in the source prediction for the random forest and 0.933 (95% CI: 0.92-0.94) for the logit boost algorithm. Logit boost algorithm was most accurate (valid accuracy: 92%, CI: 0.8706-0.9579) and predicted the origin of 81% of the domestic sporadic human salmonellosis cases. The most important source was Danish produced pigs (53%) followed by imported pigs (16%), imported broilers (6%), imported ducks (2%), Danish produced layers (2%), Danish produced cattle and imported cattle (<1%) while 18% was not predicted. Machine learning has potential for improving source attribution modeling based on sequence data. Results of such models can inform risk managers to identify and prioritize food safety interventions.

Source Attribution of Salmonella in Macadamia Nuts to Animal and Environmental Reservoirs in Queensland, Australia.

Salmonella enterica is a common contaminant of macadamia nut kernels in the subtropical state of Queensland (QLD), Australia. We hypothesized that nonhuman sources in the plantation environment contaminate macadamia nuts. We applied a modified Hald source attribution model to attribute Salmonella serovars and phage types detected on macadamia nuts from 1998 to 2017 to specific animal and environmental sources. Potential sources were represented by Salmonella types isolated from avian, companion animal, biosolids-soil-compost, equine, porcine, poultry, reptile, ruminant, and wildlife samples by the QLD Health reference laboratory. Two attribution models were applied: model 1 merged data across 1998-2017, whereas model 2 pooled data into 5-year time intervals. Model 1 attributed 47% (credible interval, CrI: 33.6-60.8) of all Salmonella detections on macadamia nuts to biosolids-soil-compost. Wildlife and companion animals were found to be the second and third most important contamination sources, respectively. Results from model 2 showed that the importance of the different sources varied between the different time periods; for example, Salmonella contamination from biosolids-soil-compost varied from 4.4% (CrI: 0.2-11.7) in 1998-2002 to 19.3% (CrI: 4.6-39.4) in 2003-2007, and the proportion attributed to poultry varied from 4.8% (CrI: 1-11) in 2008-2012 to 24% (CrI: 11.3-40.7) in 2013-2017. Findings suggest that macadamia nuts were contaminated by direct transmission from animals with access to the plantations (e.g., wildlife and companion animals) or from indirect transmission from animal reservoirs through biosolids-soil-compost. The findings from this study can be used to guide environmental and wildlife sampling and analysis to further investigate routes of Salmonella contamination of macadamia nuts and propose control options to reduce potential risk of human salmonellosis.

Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.

Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and virulence among strains. The potential of machine learning algorithms for predicting the risk/health burden at the population level while inputting large and complex NGS data was explored with Listeria monocytogenes as a case study. Listeria data consisted of a percentage similarity matrix from genome assemblies of 38 and 207 strains of clinical and food origin, respectively. Basic Local Alignment (BLAST) was used to align the assemblies against a database of 136 virulence and stress resistance genes. The outcome variable was frequency of illness, which is the percentage of reported cases associated with each strain. These frequency data were discretized into seven ordinal outcome categories and used for supervised machine learning and model selection from five ensemble algorithms. There was no significant difference in accuracy between the models, and support vector machine with linear kernel was chosen for further inference (accuracy of 89% [95% CI: 68%, 97%]). The virulence genes FAM002725, FAM002728, FAM002729, InlF, InlJ, Inlk, IisY, IisD, IisX, IisH, IisB, lmo2026, and FAM003296 were important predictors of higher frequency of illness. InlF was uniquely truncated in the sequence type 121 strains. Most important risk predictor genes occurred at highest prevalence among strains from ready-to-eat, dairy, and composite foods. We foresee that the findings and approaches described offer the potential for rethinking the current approaches in MRA.

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters.

Assessing the Effectiveness of On-Farm and Abattoir Interventions in Reducing Pig Meat-Borne Salmonellosis within E.U. Member States.

As part of the evidence base for the development of national control plans for Salmonella spp. in pigs for E.U. Member States, a quantitative microbiological risk assessment was funded to support the scientific opinion required by the EC from the European Food Safety Authority. The main aim of the risk assessment was to assess the effectiveness of interventions implemented on-farm and at the abattoir in reducing human cases of pig meat-borne salmonellosis, and how the effects of these interventions may vary across E.U. Member States. Two case study Member States have been chosen to assess the effect of the interventions investigated. Reducing both breeding herd and slaughter pig prevalence were effective in achieving reductions in the number of expected human illnesses in both case study Member States. However, there is scarce evidence to suggest which specific on-farm interventions could achieve consistent reductions in either breeding herd or slaughter pig prevalence. Hypothetical reductions in feed contamination rates were important in reducing slaughter pig prevalence for the case study Member State where prevalence of infection was already low, but not for the high-prevalence case study. The most significant reductions were achieved by a 1- or 2-log decrease of Salmonella contamination of the carcass post-evisceration; a 1-log decrease in average contamination produced a 90% reduction in human illness. The intervention analyses suggest that abattoir intervention may be the most effective way to reduce human exposure to Salmonella spp. However, a combined farm/abattoir approach would likely have cumulative benefits. On-farm intervention is probably most effective at the breeding-herd level for high-prevalence Member States; once infection in the breeding herd has been reduced to a low enough level, then feed and biosecurity measures would become increasingly more effective.

A Quantitative Microbiological Risk Assessment for Salmonella in Pigs for the European Union.

A farm-to-consumption quantitative microbiological risk assessment (QMRA) for Salmonella in pigs in the European Union has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of hypothetical reductions of slaughter-pig prevalence and the impact of control measures on the risk of human Salmonella infection. A key consideration during the QMRA development was the characterization of variability between E.U. Member States (MSs), and therefore a generic MS model was developed that accounts for differences in pig production, slaughterhouse practices, and consumption patterns. To demonstrate the parameterization of the model, four case study MSs were selected that illustrate the variability in production of pork meat and products across MSs. For the case study MSs the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types considered (pork cuts, minced meat, and fermented ready-to-eat sausages). Further analyses of the farm-to-consumption QMRA suggest that the vast majority of human risk derives from infected pigs with a high concentration of Salmonella in their feces (≥10(4) CFU/g). Therefore, it is concluded that interventions should be focused on either decreasing the level of Salmonella in the feces of infected pigs, the introduction of a control step at the abattoir to reduce the transfer of feces to the exterior of the pig, or a control step to reduce the level of Salmonella on the carcass post-evisceration.

Application of Molecular Typing Results in Source Attribution Models: The Case of Multiple Locus Variable Number Tandem Repeat Analysis (MLVA) of Salmonella Isolates Obtained from Integrated Surveillance in Denmark.

Salmonella is an important cause of bacterial foodborne infections in Denmark. To identify the main animal-food sources of human salmonellosis, risk managers have relied on a routine application of a microbial subtyping-based source attribution model since 1995. In 2013, multiple locus variable number tandem repeat analysis (MLVA) substituted phage typing as the subtyping method for surveillance of S. Enteritidis and S. Typhimurium isolated from animals, food, and humans in Denmark. The purpose of this study was to develop a modeling approach applying a combination of serovars, MLVA types, and antibiotic resistance profiles for the Salmonella source attribution, and assess the utility of the results for the food safety decisionmakers. Full and simplified MLVA schemes from surveillance data were tested, and model fit and consistency of results were assessed using statistical measures. We conclude that loci schemes STTR5/STTR10/STTR3 for S. Typhimurium and SE9/SE5/SE2/SE1/SE3 for S. Enteritidis can be used in microbial subtyping-based source attribution models. Based on the results, we discuss that an adjustment of the discriminatory level of the subtyping method applied often will be required to fit the purpose of the study and the available data. The issues discussed are also considered highly relevant when applying, e.g., extended multi-locus sequence typing or next-generation sequencing techniques.

Characterization of the Human Risk of Salmonellosis Related to Consumption of Pork Products in Different E.U. Countries Based on a QMRA.

In response to the European Food Safety Authority's wish to assess the reduction of human cases of salmonellosis by implementing control measures at different points in the farm-to-consumption chain for pork products, a quantitative microbiological risk assessment (QMRA) was developed. The model simulated the occurrence of Salmonella from the farm to consumption of pork cuts, minced meat, and fermented ready-to-eat sausage, respectively, and a dose-response model was used to estimate the probability of illness at consumption. The QMRA has a generic structure with a defined set of variables, whose values are changed according to the E.U. member state (MS) of interest. In this article we demonstrate the use of the QMRA in four MSs, representing different types of countries. The predicted probability of illness from the QMRA was between 1 in 100,000 and 1 in 10 million per serving across all three product types. Fermented ready-to-eat sausage imposed the highest probability of illness per serving in all countries, whereas the risks per serving of minced meat and pork chops were similar within each MS. For each of the products, the risk varied by a factor of 100 between the four MSs. The influence of lack of information for different variables was assessed by rerunning the model with alternative, more extreme, values. Out of the large number of uncertain variables, only a few of them have a strong influence on the probability of illness, in particular those describing the preparation at home and consumption.

World Health Organization Global Estimates and Regional Comparisons of the Burden of Foodborne Disease in 2010.

Illness and death from diseases caused by contaminated food are a constant threat to public health and a significant impediment to socio-economic development worldwide. To measure the global and regional burden of foodborne disease (FBD), the World Health Organization (WHO) established the Foodborne Disease Burden Epidemiology Reference Group (FERG), which here reports their first estimates of the incidence, mortality, and disease burden due to 31 foodborne hazards. We find that the global burden of FBD is comparable to those of the major infectious diseases, HIV/AIDS, malaria and tuberculosis. The most frequent causes of foodborne illness were diarrheal disease agents, particularly norovirus and Campylobacter spp. Diarrheal disease agents, especially non-typhoidal Salmonella enterica, were also responsible for the majority of deaths due to FBD. Other major causes of FBD deaths were Salmonella Typhi, Taenia solium and hepatitis A virus. The global burden of FBD caused by the 31 hazards in 2010 was 33 million Disability Adjusted Life Years (DALYs); children under five years old bore 40% of this burden. The 14 subregions, defined on the basis of child and adult mortality, had considerably different burdens of FBD, with the greatest falling on the subregions in Africa, followed by the subregions in South-East Asia and the Eastern Mediterranean D subregion. Some hazards, such as non-typhoidal S. enterica, were important causes of FBD in all regions of the world, whereas others, such as certain parasitic helminths, were highly localised. Thus, the burden of FBD is borne particularly by children under five years old-although they represent only 9% of the global population-and people living in low-income regions of the world. These estimates are conservative, i.e., underestimates rather than overestimates; further studies are needed to address the data gaps and limitations of the study. Nevertheless, all stakeholders can contribute to improvements in food safety throughout the food chain by incorporating these estimates into policy development at national and international levels.

World Health Organization Estimates of the Global and Regional Disease Burden of 22 Foodborne Bacterial, Protozoal, and Viral Diseases, 2010: A Data Synthesis.

BACKGROUND: Foodborne diseases are important worldwide, resulting in considerable morbidity and mortality. To our knowledge, we present the first global and regional estimates of the disease burden of the most important foodborne bacterial, protozoal, and viral diseases. METHODS AND FINDINGS: We synthesized data on the number of foodborne illnesses, sequelae, deaths, and Disability Adjusted Life Years (DALYs), for all diseases with sufficient data to support global and regional estimates, by age and region. The data sources included varied by pathogen and included systematic reviews, cohort studies, surveillance studies and other burden of disease assessments. We sought relevant data circa 2010, and included sources from 1990-2012. The number of studies per pathogen ranged from as few as 5 studies for bacterial intoxications through to 494 studies for diarrheal pathogens. To estimate mortality for Mycobacterium bovis infections and morbidity and mortality for invasive non-typhoidal Salmonella enterica infections, we excluded cases attributed to HIV infection. We excluded stillbirths in our estimates. We estimate that the 22 diseases included in our study resulted in two billion (95% uncertainty interval [UI] 1.5-2.9 billion) cases, over one million (95% UI 0.89-1.4 million) deaths, and 78.7 million (95% UI 65.0-97.7 million) DALYs in 2010. To estimate the burden due to contaminated food, we then applied proportions of infections that were estimated to be foodborne from a global expert elicitation. Waterborne transmission of disease was not included. We estimate that 29% (95% UI 23-36%) of cases caused by diseases in our study, or 582 million (95% UI 401-922 million), were transmitted by contaminated food, resulting in 25.2 million (95% UI 17.5-37.0 million) DALYs. Norovirus was the leading cause of foodborne illness causing 125 million (95% UI 70-251 million) cases, while Campylobacter spp. caused 96 million (95% UI 52-177 million) foodborne illnesses. Of all foodborne diseases, diarrheal and invasive infections due to non-typhoidal S. enterica infections resulted in the highest burden, causing 4.07 million (95% UI 2.49-6.27 million) DALYs. Regionally, DALYs per 100,000 population were highest in the African region followed by the South East Asian region. Considerable burden of foodborne disease is borne by children less than five years of age. Major limitations of our study include data gaps, particularly in middle- and high-mortality countries, and uncertainty around the proportion of diseases that were foodborne. CONCLUSIONS: Foodborne diseases result in a large disease burden, particularly in children. Although it is known that diarrheal diseases are a major burden in children, we have demonstrated for the first time the importance of contaminated food as a cause. There is a need to focus food safety interventions on preventing foodborne diseases, particularly in low- and middle-income settings.

Source attribution of human salmonellosis: an overview of methods and estimates.

Reducing the burden of foodborne salmonellosis is challenging. It requires identification of the most important food sources causing disease and prioritization of effective intervention strategies. For this purpose, a variety of methods to estimate the relative contribution of different sources of Salmonella infections have been applied worldwide. Each has strengths and limitations, and the usefulness of each depends on the public health questions being addressed. In this study, we reviewed the source attribution methods and outcomes of several studies developed in different countries and settings, comparing approaches and regional differences in attribution estimates. Reviewed results suggest that illnesses and outbreaks are most commonly attributed to exposure to contaminated food, and that eggs, broiler chickens, and pigs are among the top sources. Although most source attribution studies do not attribute salmonellosis to produce, outbreak data in several countries suggest that exposure to raw vegetables is also an important source. International travel was also a consistently important exposure in several studies. Still, the relative contribution of specific sources to human salmonellosis varied substantially between studies. Although differences in data inputs, methods, and the point in the food system where attribution was estimated contribute to variability between studies, observed differences also suggest regional differences in the epidemiology of salmonellosis.

Prevalence of Protozoan Pathogens Among Diarrheic Children Under 5 Years in Public Hospital of Ethiopia During the Global COVID 19 Pandemic.

Acute childhood diarrhea is one of the leading causes of childhood morbidity and mortality in sub-Saharan African countries. Entamoeba histolytica and Giardia lamblia are the common cause of childhood diarrhea in the region. However, there are only few studies on protozoa causing diarrhea in sub-Saharan African countries. This study was conducted to investigate the relative prevalence and explore risk factors of E. histolytica and G. lamblia among diarrheic children of under 5 years in a public hospital of Ethiopia. A retrospective study was conducted among diarrheic children at Hiwot Fana hospital, Ethiopia. Records of all diarrheic children less than 5 years who had sought medical treatment in the hospital from September 1, 2020 to December 31, 2022 were included. Data were collected from 1257 medical records of the children using a structured data-collection format. Data were entered into an Excel sheet and exported into SPSS version 22 for data processing and analysis. Descriptive statistical tests, Chi-square, and logistic region analysis were applied to determine predictors of protozoa infections. Of the 1257 cases, 962 (76.5%) had watery diarrhea and the remaining 239 (19.0%) had dysentery. The combined prevalence of E. histolytica and G. lamblia among diarrheic children was 11.8% (95% CI: 9.6-13.4). As the age of children increased, the frequency of these two protozoan infections was significantly increased compared to children with other causes. There were more diarrhea cases during the summer season including those associated with E. histolytica and G. lamblia. This study revealed that 1 in 10 causes of diarhhea among young children in the study area was likely caused by E. histolytica and G. lamblia. These findings call for community-based safe water and food safety interventions in order to reduce childhood diarrhea caused by protozoan infections in resource-poor settings.

Occurrence of Diarrheagenic Pathogens and Their Coinfection Profiles in Diarrheic Under Five Children and Tracked Human Contacts in Urban and Rural Settings of Eastern Ethiopia.

Diarrheagenic Escherichia coli, Campylobacter, Nontyphoidal Salmonella, and Shigella are common cause of childhood diarrhea in countries like Ethiopia, but data on their sources and coinfection profiles is limited. A cross sectional study was conducted from November 2021 to January 2023 to determine the prevalence, coinfection, and monthly occurrence rates of major diarrheagenic bacteria in diarrheic under five children and asymptomatic contacts at urban and rural settings in Ethiopia. A total of 345 stool samples were collected from; 262 diarrheic children visiting Hiwot Fana Hospital, Kersa, and Adelle Health Centers; and 83 caretakers and siblings through case based contact tracing. Samples were analyzed using standard laboratory procedures and the overall prevalence of enteric pathogens was 26.96%, with the highest isolation rate during the winter and peaks of 73.91% in February. The occurrence of the pathogens in children and tracked contacts was 27.86 and 24.09%, respectively. In our study, 8.53% coinfection and 23.66% single pathogen infection was recorded in diarrheic children. The study also showed 4.51 and 3.88% of diarrhea in children from urban and rural had attributed to bacterial coinfection, respectively. The most prevalent pathogen in diarrheic children was Diarrheagenic E. coli (10.31%), and followed by Campylobacter. On the other hand, Diarrheagenic E. coli was the second dominant bacteria following Shigella in the traced contacts, with prevalence of 8.43% and 9.64%, respectively. Based on the study site, the prevalence of Diarrheagenic E. coli and Nontyphoidal Salmonella was higher in children from urban than those from rural. However, the occurrence of each pathogen had no significant differences (P > .05) between settings. The high pathogens occurrence rate in the current study indicates the need for strong control strategies and better child carrying and treatment of diarrheal diseases at both urban and rural settings. Further studies on possible sources and factors attributing to the occurrence of enteric pathogens in children are also recommended.

Analysis of reservoir sources of Campylobacter isolates to free-range broilers in Denmark.

Campylobacter is a common cause of food poisoning in many countries, with broilers being the main source. Organic and free-range broilers are more frequently Campylobacter-positive than conventionally raised broilers and may constitute a higher risk for human infections. Organic and free-range broilers may get exposed to Campylobacter from environmental reservoirs and livestock farms, but the relative importance of these sources is unknown. The aim of the study was to describe similarities and differences between the genetic diversity of the Campylobacter isolates collected from free-range/organic broilers with those isolated from conventional broilers and other animal hosts (cattle, pigs, and dogs) in Denmark to make inferences about the reservoir sources of Campylobacter to free-range broilers. The applied aggregated surveillance data consisted of sequenced Campylobacter isolates sampled in 2015 to 2017 and 2018 to 2021. The data included 1,102 isolates from free-range (n = 209), conventional broilers (n = 577), cattle (n = 261), pigs (n = 30), and dogs (n = 25). The isolates were cultivated from either fecal material (n = 434), food matrices (n = 569), or of nondisclosed origin (n = 99). Campylobacter jejuni (94.5%) dominated and subtyping analysis found 170 different sequence types (STs) grouped into 75 clonal complexes (CCs). The results suggest that CC-21 and CC-45 are the most frequent CCs found in broilers. The relationship between the CCs in the investigated sources showed that the different CCs were shared by most of the animals, but not pigs. The ST-profiles of free-range broilers were most similar to that of conventional broilers, dogs and cattle, in that order. The similarity was stronger between conventional broilers and cattle than between conventional and free-range broilers. The results suggest that cattle may be a plausible reservoir of C. jejuni for conventional and free-range broilers, and that conventional broilers are a possible source for free-range broilers or reflect a dominance of isolates adapted to the same host environment. Aggregated data provided valuable insight into the epidemiology of Campylobacter sources for free-range broilers, but time-limited sampling of isolates from different sources within a targeted area would hold a higher predictive value.

Molecular Characterization of Hetero-Pathogenic and Diarrheagenic Escherichia coli Pathotypes in Diarrheic Children under Five Years and Exposure Environment in Ogun State, South-West Nigeria.

BACKGROUND: Diarrheagenic Escherichia coli (DEC) is one of the most common etiological agents of moderate-to-severe diarrhea in Low- and Middle-Income Countries (LMICs). Therefore, determining the source(s) of DEC in index cases and exposure environment is important for developing a prevention strategy. The current study aims to investigate the prevalence of DEC among children under 5 years and their exposure environment in Ogun State, Nigeria. METHODS: Samples from 228 diarrheic children and their exposure environment were collected and screened for E. coli. Bio-chemically compatible distinct colonies were molecularly characterized using a 7-virulence-gene multiplex PCR with virulence factors (VFs) indicative of four pathotypes of E. coli: enterotoxigenic (ETEC), verotoxigenic (VTEC), enteropathogenic (EPEC), and enteroinvasive (EIEC). Representative pathotypes were subjected to antimicrobial susceptibility and over-expressed efflux pump assays. RESULTS: One or more VFs typical of specific pathotypes were detected in 25.9% (59/228) diarrhea cases consisting of ETEC (21.5%) and EPEC (0.4%), while hetero-pathogenic pathotypes were found in 4.0% of cases. Of the food sources, 27.9% (101/362) were positive for DEC, of which ETEC accounted for 21.0%, VTEC 1.9%, EPEC 0.6%, EIEC 0.6%, and hetero-pathogenic pathotypes were 3.9%. Furthermore, ETEC was the only pathotype detected in the wastewater (4/183). Interestingly, the consumption of street-vended foods was the most significant (p = 0.04) risk factor for DEC infection in the study area. A total of 73.3% of selected DEC pathotypes showed resistance to antimicrobials, while 27.5% demonstrated over-expression of efflux pump activity. CONCLUSION: The high prevalence of ETEC across all sources and the occurrence of hetero-pathogenic DEC in diarrheic children and food sources emphasizes the importance of establishing a better strategy for the control and prevention of diarrhea among children in low- and medium-income households.

Comparison of Source Attribution Methodologies for Human Campylobacteriosis.

Campylobacter spp. are the most common cause of bacterial gastrointestinal infection in humans both in Denmark and worldwide. Studies have found microbial subtyping to be a powerful tool for source attribution, but comparisons of different methodologies are limited. In this study, we compare three source attribution approaches (Machine Learning, Network Analysis, and Bayesian modeling) using three types of whole genome sequences (WGS) data inputs (cgMLST, 5-Mers and 7-Mers). We predicted and compared the sources of human campylobacteriosis cases in Denmark. Using 7mer as an input feature provided the best model performance. The network analysis algorithm had a CSC value of 78.99% and an F1-score value of 67%, while the machine-learning algorithm showed the highest accuracy (98%). The models attributed between 965 and all of the 1224 human cases to a source (network applying 5mer and machine learning applying 7mer, respectively). Chicken from Denmark was the primary source of human campylobacteriosis with an average percentage probability of attribution of 45.8% to 65.4%, representing Bayesian with 7mer and machine learning with cgMLST, respectively. Our results indicate that the different source attribution methodologies based on WGS have great potential for the surveillance and source tracking of Campylobacter. The results of such models may support decision makers to prioritize and target interventions.

High diversity of Salmonella spp. from children with diarrhea, food, and environmental sources in Kilimanjaro - Tanzania: one health approach.

Salmonella is one of the most frequent causes of diarrhea globally. This study used a One Health approach to identify Salmonella species in children admitted with diarrhea and tested samples from the cases' household environment to investigate their genetic similarity using whole genome sequencing. Surveillance of hospitalized diarrhea cases among children under 5 years was conducted in rural and urban Moshi Districts in the Kilimanjaro Region of Tanzania from July 2020 through November 2022. Household visits were conducted for every child case whose parent/caregiver provided consent. Stool samples, water, domestic animal feces, meat, and milk were collected and tested for Salmonella. Isolates were sequenced on the Illumina NextSeq platform. Multilocus Sequence Typing and phylogenetic analyses were performed to map the genetic relatedness of the isolates. Salmonella was isolated from 72 (6.0%) of 1,191 samples. The prevalence of Salmonella in children with diarrhea, domestic animal feces, food, and water was 2.6% (n = 8/306), 4.6% (n = 8/174), 4.2% (n = 16/382), and 17.3% (n = 39/225), respectively. Four (1.3%) of the 306 enrolled children had a Salmonella positive sample taken from their household. The common sequence types (STs) were ST1208, ST309, ST166, and ST473. Salmonella Newport was shared by a case and a raw milk sample taken from the same household. The study revealed a high diversity of Salmonella spp., however, we detected a Salmonella clone of ST1208 isolated at least from all types of samples. These findings contribute to understanding the epidemiology of Salmonella in the region and provide insight into potential control of foodborne diseases through a One Health approach.