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The prevalence of Campylobacter infection is generally high among children in low- and middle-income countries (LMIC), but the dynamics of its acquisition and clearance are understudied. We aim to quantify this process among children under two years old in eight LMIC using a statistical modeling approach, leveraging enzyme-immunoassay-based Campylobacter genus data and quantitative-PCR-based Campylobacter jejuni/coli data from the MAL-ED study. We developed a Markov model to compare the dynamics of acquisition and clearance of Campylobacter across countries and to explore the effect of antibiotic usage on Campylobacter clearance. Clearance rates were generally higher than acquisition rates, but their magnitude and temporal pattern varied across countries. For C. jejuni/coli, clearance was faster than acquisition throughout the two years at all sites. For Campylobacter spp., the acquisition rate either exceeded or stayed very close to the clearance rate after the first half year in Bangladesh, Pakistan and Tanzania, leading to high prevalence. Bangladesh had the shortest (28 and 57 days) while Brazil had the longest (328 and 306 days) mean times from last clearance to acquisition for Campylobacter spp. and C. jejuni/coli, respectively. South Africa had the shortest (10 and 8 days) while Tanzania had the longest (53 and 41 days) mean times to clearance for Campylobacter spp. and C. jejuni/col, respectively. The use of Macrolide accelerated clearance of C. jejuni/coli in Bangladesh and Peru and of Campylobacter spp. in Bangladesh and Pakistan. Fluoroquinolone showed statistically meaningful effects only in Bangladesh but for both Campylobacter groups. Higher prevalence of Campylobacter infection was mainly driven by a high acquisition rate that was close to or surpassing the clearance rate. Acquisition rate usually peaked in 11-17 months of age, indicating the importance of targeting the first year of life for effective interventions to reduce exposures., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Abstract: The Florida Complaint and Outbreak Reporting System (FL-CORS) database is used by the Florida Department of Health's Food and Waterborne Disease Program as one of the tools to detect foodborne disease outbreaks (FBOs). We present a descriptive and spatial network analysis of FL-CORS data collected during 2015 to 2018. We also quantified FBOs that were investigated and confirmed because of a filed complaint and the etiological agents involved in these outbreaks. An increasing number of unique complaints filed in FL-CORS was observed during 2015 to 2018, with a sharp increase during 2017 to 2018 and a different seasonal pattern in 2018. The preferred mechanism of reporting varied by age group, with younger people more frequently filing complaints online and older people preferring reporting in person or by phone. Spatial network analysis revealed that 87% of complaints had the same county of residence and county of presumed exposure. Frequency of complaints was negatively associated with linear distance between place of residence and place of exposure at the zip code level. Counties located in North and Central Florida, as well as some coastal areas in South Florida, had higher incidence rates of complaints. Those counties tend to have a large population density, and some are popular vacation destinations. On average, 96 FBOs were reported in Florida annually, of which 60% were confirmed with successful identification of the causative agent. The 56% of the confirmed FBOs were triggered by a complaint. Throughout the years, 2.4 to 2.8 FBOs and 1.4 confirmed FBOs were identified per 100 complaints. Ciguatera toxin was the cause of 40% of all FBOs in Florida, and only 28% of outbreaks were detected through complaints. In contrast, complaints were the main source of identifying outbreaks of norovirus, nontyphoidal Salmonella enterica, and scombroid food poisoning, as well as rare outbreaks of Clostridium perfringens, Cryptosporidium spp., Shigella spp., and Vibrio vulnificus., (Copyright ©, International Association for Food Protection.)

The impact of foodborne metals on the burden of disease has been largely overlooked, in comparison to the attention on acute diseases associated with infectious foodborne agents. Four articles in this special section describe in detail the burden of disease from foodborne lead, methylmercury, arsenic, and cadmium. Ingested lead and methylmercury are causally associated with lifelong intellectual disability. Long term ingestion of arsenic is causally associated with an increased risk of cancer. Long term ingestion of cadmium is causally associated with an increased risk of late stage chronic kidney disease. This article presents an overview of the burden of disease from these four foodborne metals and discusses them in the context of the World Health Organization's initiative to estimate the global burden of foodborne disease. The results indicate that in 2015, ingestion of arsenic, methylmercury, lead, and cadmium resulted in more than 1 million illnesses, over 56,000 deaths, and more than 9 million disability-adjusted life years (DALYs) worldwide. The greatest impact on DALYs was in the Western Pacific B subregion. All of the metals were found to have high DALYs per case in comparison with other foodborne disease agents, including infectious and parasitic agents. In addition, lead, arsenic, and methylmercury were found to have high DALYs per 100,000 population in comparison to other foodborne disease agents., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Several produce-borne outbreaks have been associated with the use of contaminated water during preharvest applications. Salmonella has been implicated in a number of these outbreaks. The purpose of this study was to evaluate the microbial quality of agricultural surface water used in preharvest production on the Eastern Shore of Virginia in accordance with the Food Safety Modernization Act's Produce Safety Rule water standards. The study also examined the prevalence, concentration, and diversity of Salmonella in those water sources. Water samples (1 L) from 20 agricultural ponds were collected during the 2015 and 2016 growing seasons ( n = 400). Total aerobic bacteria, total coliforms, and Escherichia coli were enumerated for each sample. Population levels of each microorganism were calculated per 100-mL sample and log transformed, when necessary. Samples (250 mL) were also enriched for Salmonella. Presumptive Salmonella isolates were confirmed by PCR ( invA gene) and were serotyped. In 2016, the concentration of Salmonella in each sample was also estimated by most probable number (MPN). Indicator bacteria and environmental and meteorological factors were analyzed for their association with the detection of a Salmonella-positive water sample by using logistic regression analysis. Seventeen of the 20 ponds met the Food Safety Modernization Act's Produce Safety Rule standards for production agricultural water. Three ponds did not meet the standards because the statistical threshold value exceeded the limit. Salmonella was detected in 19% of water samples in each year (38 of 200 in 2015 and 38 of 200 in 2016). Of the 118 Salmonella isolates serotyped, 14 serotypes were identified with the most prevalent being Salmonella Newport. E. coli concentration, farm, and total aerobic bacteria concentration were significantly associated with the likelihood of detecting a Salmonella-positive sample The average concentration of Salmonella in all samples was 4.44 MPN/100 mL, with the limit of detection being 3.00 MPN/100 mL. The highest concentration of Salmonella was 93.0 MPN/100 mL. These data will assist in a better understanding of the risks that production water poses to produce contamination events.

Microbial contamination of fresh produce (fresh fruits and vegetables) poses serious public health concerns worldwide. This study was conducted as a comprehensive analysis of biological hazards in the global fresh produce chain. Data about produce-related outbreaks and illness were collected from the annual reports and databases of foodborne outbreak surveillance systems in different regions and countries from 2010 to 2015. The global patterns of and regional differences in documented outbreaks and cases were analyzed, and produce commodities and pathogens of greatest concern were identified. Data on sporadic illnesses were also collected through a comprehensive literature review of case-control studies. We found 988 produce-related outbreaks (with known agents) and 45,723 cases in all regions and countries. The numbers of produce-related outbreaks per million person-years were approximately 0.76, 0.26, 0.25, 0.13, 0.12, and 0.05 in New Zealand, Australia, the United States, the European Union, Canada, and Japan, respectively. The top three food categories and pathogens contributing to produce-related outbreaks were vegetables and nonfruits (i.e., food other than fruits; 27.0%), unspecified vegetables (12.2%), and vegetable row crops (11.7%) and norovirus (42.4%), Salmonella enterica (19.9%), and Staphylococcus aureus (7.9%), respectively. Produce consumption was identified as a protective factor, a risk factor, and either a protective or risk factor for sporadic illnesses in 11, 5, and 5 studies, respectively, among 21 case-control studies. Risks associated with produce consumption in the United States and the European Union have been linked to various factors such as irrigation water, cross-contamination, storage time and temperature abuse, infected food handlers, and unprocessed contaminated ingredients. The results of the current study indicate the complexity of produce products consumed across the globe and the difficulty in tracing illnesses back to specific food ingredients.

The U.S. Food and Drug Administration (FDA) has defined standards for the microbial quality of agricultural surface water used for irrigation. According to the FDA produce safety rule (PSR), a microbial water quality profile requires analysis of a minimum of 20 samples for Escherichia coli over 2 to 4 years. The geometric mean (GM) level of E. coli should not exceed 126 CFU/100 mL, and the statistical threshold value (STV) should not exceed 410 CFU/100 mL. The water quality profile should be updated by analysis of a minimum of five samples per year. We used an extensive set of data on levels of E. coli and other fecal indicator organisms, the presence or absence of Salmonella, and physicochemical parameters in six agricultural irrigation ponds in West Central Florida to evaluate the empirical and theoretical basis of this PSR. We found highly variable log-transformed E. coli levels, with standard deviations exceeding those assumed in the PSR by up to threefold. Lognormal distributions provided an acceptable fit to the data in most cases but may underestimate extreme levels. Replacing censored data with the detection limit of the microbial tests underestimated the true variability, leading to biased estimates of GM and STV. Maximum likelihood estimation using truncated lognormal distributions is recommended. Twenty samples are not sufficient to characterize the bacteriological quality of irrigation ponds, and a rolling data set of five samples per year used to update GM and STV values results in highly uncertain results and delays in detecting a shift in water quality. In these ponds, E. coli was an adequate predictor of the presence of Salmonella in 150-mL samples, and turbidity was a second significant variable. The variability in levels of E. coli in agricultural water was higher than that anticipated when the PSR was finalized, and more detailed information based on mechanistic modeling is necessary to develop targeted risk management strategies., (Copyright ©, International Association for Food Protection.)

Outbreaks of human illness caused by enteric pathogens such as Salmonella are increasingly linked to the consumption of fruits and vegetables. Knowledge on the factors affecting Salmonella proliferation on fresh produce therefore becomes increasingly important to safeguard public health. Previous experiments showed a limited impact of pre-harvest production practices on Salmonella proliferation on tomatoes, but suggested a significant effect of harvest time. We explored the data from two previously published and one unpublished experiment using regression trees, which allowed overcoming the interpretational difficulties of classical statistical models with higher order interactions. We assessed the effect of harvest time by explicitly modeling the climatic conditions at harvest time and by performing confirmatory laboratory experiments. Across all datasets, regression trees confirmed the dominant effect of harvest time on Salmonella proliferation, with humidity-related factors emerging as the most important underlying climatic factors. High relative humidity the week prior to harvest was consistently associated with lower Salmonella proliferation. A controlled lab experiment confirmed that tomatoes containing their native epimicrobiota supported significantly lower Salmonella proliferation when incubated at higher humidity prior to inoculation. The complex interactions between environmental conditions and the native microbiota of the tomato crop remain to be fully understood., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Case-control studies of outbreaks and of sporadic cases of infectious diseases may provide a biased estimate of the infection rate ratio, due to selecting controls that are not at risk of disease. We use a dynamic mathematical model to explore biases introduced in results drawn from case-control studies of enteric pathogens by waning and boosting of immunity, and by asymptomatic infections, using Campylobacter jejuni as an example. Individuals in the population are either susceptible (at risk of infection and disease), fully protected (not at risk of either) or partially protected (at risk of infection but not of disease). The force of infection is a function of the exposure frequency and the exposure dose. We show that the observed disease odds ratios are indeed strongly biased towards the null, i.e. much lower than the infection rate ratio, and furthermore even not proportional to it. The bias could theoretically be controlled by sampling controls only from the reservoir of susceptible individuals. The population at risk is in a dynamic equilibrium, and cannot be identified as those who are not and have never experienced disease. Individual-level samples to measure protective immunity would be required, complicating the design, cost and execution of case-control studies., (Copyright © 2016 The Author(s). Published by Elsevier B.V. All rights reserved.)

The aim of the study was to investigate the effect of brushing prior to scalding on reducing the E. coli and Enterobacteriaceae concentrations on carcasses. Three visits were arranged to a commercial slaughterhouse in which carcasses were cleaned in a separate line. Ten batches were sampled to compare the E. coli and Enterobacteriaceae concentrations on carcasses before and after a stand-alone brushing unit. Per batch, 8 carcasses before and 8 after brushing were sampled by the whole-carcass rinse method. Furthermore, the dry matter content and the pH were determined in these samples, as these parameters indirectly (dry matter) or directly (pH) influence the scalding lethality. Results revealed a small but statistically significant reduction (P < 0.001) in E. coli and Enterobacteriaceae concentrations on the brushed carcasses. The concentrations on whole carcasses were reduced on average by 0.3 log for both E. coli and Enterobacteriaceae. Rinse samples from treated carcasses had significantly less dry matter on average by 2.5 g (P < 0.001) and significantly higher pH by 0.08 units (P < 0.001). Although these differences are statistically significant, they might have rather low biological relevance; thus, further optimization of brushes is needed for more relevant results. This study confirms that brushing reduces bacterial concentrations on carcasses, which may be increased potentially by enlarging the brushed surface of the carcass. Further in-line investigations are needed to observe the effect of brushing on bacterial concentrations in scalding water and on carcasses after scalding and at the end of processing., (© 2016 Poultry Science Association Inc.)

This study aimed at identifying explanatory variables that were associated with Campylobacter and Escherichia coli concentrations throughout processing in two commercial broiler slaughterhouses. Quantative data on Campylobacter and E. coli along the processing line were collected. Moreover, information on batch characteristics, slaughterhouse practices, process performance, and environmental variables was collected through questionnaires, observations, and measurements, resulting in data on 19 potential explanatory variables. Analysis was conducted separately in each slaughterhouse to identify which variables were related to changes in concentrations of Campylobacter and E. coli during the processing steps: scalding, defeathering, evisceration, and chilling. Associations with explanatory variables were different in the slaughterhouses studied. In the first slaughterhouse, there was only one significant association: poorer uniformity of the weight of carcasses within a batch with less decrease in E. coli concentrations after defeathering. In the second slaughterhouse, significant statistical associations were found with variables, including age, uniformity, average weight of carcasses, Campylobacter concentrations in excreta and ceca, and E. coli concentrations in excreta. Bacterial concentrations in excreta and ceca were found to be the most prominent variables, because they were associated with concentration on carcasses at various processing points. Although the slaughterhouses produced specific products and had different batch characteristics and processing parameters, the effect of the significant variables was not always the same for each slaughterhouse. Therefore, each slaughterhouse needs to determine its particular relevant measures for hygiene control and process management. This identification could be supported by monitoring changes in bacterial concentrations during processing in individual slaughterhouses. In addition, the possibility that management and food handling practices in slaughterhouses contribute to the differences in bacterial contamination between slaughterhouses needs further investigation.

Mouse models have been extensively used to investigate the mechanisms of salmonellosis. However, the role of the hosts' local intestinal responses during early stages of infection remain unclear. In this study, transcript array analysis was employed to investigate regulation of gene expression in the murine intestine following oral challenge with Salmonella enterica serovar Enteritidis. Salmonella resistant C3H/HeN mice elicited only weak transcription responses in the ileum even in the presence of bacterial replication and systemic infection. This poor response was surprising given previously published results using in vitro models. Susceptible TLR4-deficient C3H/HeJ mice displayed a stronger response, suggesting a role for TLR4 in dampening the response to Salmonella. Responses of susceptible BALB/c mice were also unremarkable. In contrast, in vitro infection of murine rectal epithelial cells induced a strong transcription response consistent with previous in vitro studies. Although the pattern of genes expressed by the ileal tissue upon in vivo infection were similar in all three mouse lines, the genes up-regulated during in vitro infection were different, indicating that the responses seen in vitro do not mimic those seen in vivo. Taken together these data indicate that in vivo responses to Salmonella, at the level of the intestine, are tightly regulated by the host., (Copyright © 2011 Institut Pasteur. All rights reserved.)