Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Salmonella is a leading cause of foodborne illness (i.e., salmonellosis) outbreaks, which on occasion are attributed to ground turkey. The poultry industry uses Salmonella prevalence as an indicator of food safety. However, Salmonella prevalence is only one of several factors that determine risk of salmonellosis. Consequently, a model for predicting risk of salmonellosis from individual lots of ground turkey as a function of Salmonella prevalence and other risk factors was developed. Data for Salmonella contamination (prevalence, number, and serotype) of ground turkey were collected at meal preparation. Scenario analysis was used to evaluate effects of model variables on risk of salmonellosis. Epidemiological data were used to simulate Salmonella serotype virulence in a dose‐response model that was based on human outbreak and feeding trial data. Salmonella prevalence was 26% (n = 100) per 25 g of ground turkey, whereas Salmonella number ranged from 0 to 1.603 with a median of 0.185 log per 25 g. Risk of salmonellosis (total arbitrary units (AU) per lot) was affected (p ≤ 0.05) by Salmonella prevalence, number, and virulence, by incidence and extent of undercooking, and by food consumption behavior and host resistance but was not (p > 0.05) affected by serving size, serving size distribution, or total bacterial load of ground turkey when all other risk factors were held constant. When other risk factors were not held constant, Salmonella prevalence was not correlated (r = ?0.39; p = 0.21) with risk of salmonellosis. Thus, Salmonella prevalence alone was not a good indicator of poultry food safety because other factors were found to alter risk of salmonellosis. In conclusion, a more holistic approach to poultry food safety, such as the process risk model developed in the present study, is needed to better protect public health from foodborne pathogens like Salmonella.     

Leveraging risk assessment for foodborne outbreak investigations: The Quantitative Risk Assessment-Epidemic Curve Prediction Model

Root cause analysis can be used in foodborne illness outbreak investigations to determine the underlying causes of an outbreak and to help identify actions that could be taken to prevent future outbreaks. We developed a new tool, the Quantitative Risk Assessment-Epidemic Curve Prediction Model (QRA-EC), to assist with these goals and applied it to a case study to investigate and illustrate the utility of leveraging quantitative risk assessment to provide unique insights for foodborne illness outbreak root cause analysis. We used a 2019 Salmonella outbreak linked to melons as a case study to demonstrate the utility of this model (Centers for Disease Control and Prevention [CDC], 2019). The model was used to evaluate the impact of various root cause hypotheses (representing different contamination sources and food safety system failures in the melon supply chain) on the predicted number and timeline of illnesses. The predicted number of illnesses varied by contamination source and was strongly impacted by the prevalence and level of Salmonella contamination on the surface/inside of whole melons and inside contamination niches on equipment surfaces. The timeline of illnesses was most strongly impacted by equipment sanitation efficacy for contamination niches. Evaluations of a wide range of scenarios representing various potential root causes enabled us to identify which hypotheses, were likely to result in an outbreak of similar size and illness timeline to the 2019 Salmonella melon outbreak. The QRA-EC framework can be adapted to accommodate any food–pathogen pairs to provide insights for foodborne outbreak investigations.     

Development of a Self‐Regulated Dynamic Model for the Propagation of Salmonella Typhimurium in Pig Farms

A self‐regulated epidemic model was developed to describe the dynamics of Salmonella Typhimurium in pig farms and predict the prevalence of different risk groups at slaughter age. The model was focused at the compartment level of the pig farms and it included two syndromes, a high and a low propagation syndrome. These two syndromes generated two different classes of pigs, the High Infectious and the Low Infectious, respectively, which have different shedding patterns. Given the two different classes and syndromes, the Infectious Equivalent concept was used, which reflected the combination of High and Low Infectious pigs needed for the high propagation syndrome to be triggered. Using the above information a new algorithm was developed that decides, depending on the Infectious Equivalent, which of the two syndromes should be triggered. Results showed that the transmission rate of S. Typhimurium for the low propagation syndrome is around 0.115, pigs in Low Infectious class contribute to the transmission of the infection by 0.61–0.80 of pigs in High Infectious class and that the Infectious Equivalent should be above 10–14% of the population in order for the high propagation syndrome to be triggered. This self‐regulated dynamic model can predict the prevalence of the classes and the risk groups of pigs at slaughter age for different starting conditions of infection.     

Evaluation of Scenarios for Reducing Human Salmonellosis Through Household Consumption of Fresh Minced Pork Meat

Nontyphoidal salmonellosis is the second most frequently reported zoonotic disease in the European Union (EU) and is considered to be a major threat to human health worldwide. The most reported Salmonella serovar in the EU is S. Enteritidis, mainly associated with egg contamination, followed by S. Typhimurium, with the latter being the most predominant serovar isolated from pork. These findings suggest that reducing the Salmonella contamination in the pork production might be a good strategy to prevent and control human salmonellosis in the EU. Recently, a quantitative microbial risk assessment (QMRA) has been developed to assess the risks for human salmonellosis due to home consumption of fresh minced pork meat in Belgium.⁽ 1 ⁾ The newly developed risk model is called the METZOON model. In the current study, the METZOON model was used to evaluate the effectiveness of different hypothetical Salmonella mitigation strategies implemented at different stages of the minced pork production and consumption chain by means of a scenario analysis. To efficiently evaluate the mitigation strategies, model results were obtained by running simulations using the randomized complete block design. The effectiveness of a mitigation strategy is expressed using point and interval estimates of the effect size for dependent observations, expressed as the standardized difference in population means. The results indicate that the most effective strategies are taken during the slaughter processes of polishing, evisceration, and chilling, and during postprocessing, whereas interventions in the primary production and at the beginning of the slaughter process seem to have only a limited effect. Improving consumer awareness is found to be effective as well.     

A Practical Framework for the Construction of a Biotracing Model: Application to Salmonella in the Pork Slaughter Chain

A novel purpose of the use of mathematical models in quantitative microbial risk assessment (QMRA) is to identify the sources of microbial contamination in a food chain (i.e., biotracing). In this article we propose a framework for the construction of a biotracing model, eventually to be used in industrial food production chains where discrete numbers of products are processed that may be contaminated by a multitude of sources. The framework consists of steps in which a Monte Carlo model, simulating sequential events in the chain following a modular process risk modeling (MPRM) approach, is converted to a Bayesian belief network (BBN). The resulting model provides a probabilistic quantification of concentrations of a pathogen throughout a production chain. A BBN allows for updating the parameters of the model based on observational data, and global parameter sensitivity analysis is readily performed in a BBN. Moreover, a BBN enables “backward reasoning” when downstream data are available and is therefore a natural framework for answering biotracing questions. The proposed framework is illustrated with a biotracing model of Salmonella in the pork slaughter chain, based on a recently published Monte Carlo simulation model. This model, implemented as a BBN, describes the dynamics of Salmonella in a Dutch slaughterhouse and enables finding the source of contamination of specific carcasses at the end of the chain.     

Interventions Targeting Deep Tissue Lymph Nodes May Not Effectively Reduce the Risk of Salmonellosis from Ground Pork Consumption: A Quantitative Microbial Risk Assessment

The inclusion of deep tissue lymph nodes (DTLNs) or nonvisceral lymph nodes contaminated with Salmonella in wholesale fresh ground pork (WFGP) production may pose risks to public health. To assess the relative contribution of DTLNs to human salmonellosis occurrence associated with ground pork consumption and to investigate potential critical control points in the slaughter‐to‐table continuum for the control of human salmonellosis in the United States, a quantitative microbial risk assessment (QMRA) model was established. The model predicted an average of 45 cases of salmonellosis (95% CI = [19, 71]) per 100,000 Americans annually due to WFGP consumption. Sensitivity analysis of all stochastic input variables showed that cooking temperature was the most influential parameter for reducing salmonellosis cases associated with WFGP meals, followed by storage temperature and Salmonella concentration on contaminated carcass surface before fabrication. The input variables were grouped to represent three main factors along the slaughter‐to‐table chain influencing Salmonella doses ingested via WFGP meals: DTLN‐related factors, factors at processing other than DTLNs, and consumer‐related factors. The evaluation of the impact of each group of factors by second‐order Monte Carlo simulation showed that DTLN‐related factors had the lowest impact on the risk estimate among the three groups of factors. These findings indicate that interventions to reduce Salmonella contamination in DTLNs or to remove DTLNs from WFGP products may be less critical for reducing human infections attributable to ground pork than improving consumers’ cooking habits or interventions of carcass decontamination at processing.     

Assessing the effect on the public health risk of current and alternative border control of Salmonella Typhimurium and Enteritidis in imported frozen poultry meat in Jordan

The JFDA applies border control for Salmonella Typhimurium and Salmonella Enteritidis in frozen poultry products. A QMRA model was developed to evaluate the effectiveness of this system in controlling the risk for consumers. The model consists of three modules; consumer phase, risk estimation, and risk reduction. The model inputs were the occurrence of Salmonella in different types of imported poultry products, the LOD of the Rapid’Salmonella, the number of tested samples of each batch, and the criteria for rejection. The model outputs were public health impact as the Minimum Relative Residual Risk (MRRR) given the batches’ refusal and the percentage of Batches that are Not-compliant with the Microbiological Criteria (BNMC) of rejection. To estimate the overall MRRR of the border control, the estimated country and product-specific MRRR were summarized and weighted by the total imports of each product from each country. The current border control based on one sample per batch gives an overall MRRR value of 27%. The alternative scenarios based on three and five samples per batch are 12% and 8%, respectively. Overall, the higher the prevalence and/or concentration of Salmonella in imported products, the more the likelihood that batches will be rejected. For products with up-to-date data of occurrence, the estimated BNMC was similar to the observed proportion of rejected batches. The lack of data on the Salmonella concentrations in poultry products from different countries is the major source of the uncertainties in the model. It reduces our opportunities to obtain valid estimates of the absolute risk.     

Modeling of interventions for reducing external Enterobacteriaceae contamination of broiler carcasses during processing

This article presents a mathematical model for the Enterobacteriaceae count on the surface of broiler chicken during slaughter and how it may be affected by different processing technologies. The model is based on a model originally developed for Campylobacter and has been adapted for Enterobacteriaceae using a Bayesian updating approach and hitherto unpublished data gathered from German abattoirs. The slaughter process in the model consists of five stages: input, scalding, defeathering, evisceration, washing, and chilling. The impact of various processing technologies along the broiler processing line on the Enterobacteriaceae count on the carcasses’ surface has been determined from literature data. The model is implemented in the software R and equipped with a graphical user interface which allows interactively to choose among different processing technologies for each stage along the processing line. Based on the choice of processing technologies the model estimates the Enterobacteriaceae count on the surface of each broiler chicken at each stage of processing. This result is then compared to a so-called baseline model which simulates a processing line with a fixed set of processing technologies. The model calculations showed how even very effective removal of bacteria on the exterior of the carcass in a previous step will be undone by the cross-contamination with leaked feces, if feces contain high concentrations of bacteria.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

A Risk Assessment of Campylobacteriosis and Salmonellosis Linked to Chicken Meals Prepared in Households in Dakar,Senegal

We used a quantitative microbiological risk assessment model to describe the risk of Campylobacter and Salmonella infection linked to chicken meals prepared in households in Dakar, Senegal. The model uses data collected specifically for this study, such as the prevalence and level of bacteria on the neck skin of chickens bought in Dakar markets, time‐temperature profiles recorded from purchase to consumption, an observational survey of meal preparation in private kitchens, and detection and enumeration of pathogens on kitchenware and cooks’ hands. Thorough heating kills all bacteria present on chicken during cooking, but cross‐contamination of cooked chicken or ready‐to‐eat food prepared for the meal via kitchenware and cooks’ hands leads to a high expected frequency of pathogen ingestion. Additionally, significant growth of Salmonella is predicted during food storage at ambient temperature before and after meal preparation. These high exposures lead to a high estimated risk of campylobacteriosis and/or salmonellosis in Dakar households. The public health consequences could be amplified by the high level of antimicrobial resistance of Salmonella and Campylobacter observed in this setting. A significant decrease in the number of ingested bacteria and in the risk could be achieved through a reduction of the prevalence of chicken contamination at slaughter, and by the use of simple hygienic measures in the kitchen. There is an urgent need to reinforce the hygiene education of food handlers in Senegal.     

Assessing Interventions to Reduce the Risk of Campylobacter Prevalence in Broilers

As part of a comprehensive risk assessment on the Campylobacter prevalence in the chicken production chain (from young born chicken till chicken fillet) in the Netherlands, we formulated a quantitative model on the transmission dynamics of Campylobacter at Dutch broiler farms. This model is used to quantify the risk of Campylobacter prevalence in broilers at the time that flocks leave the farm for processing. To this end, we assumed that the Campylobacter prevalence is primarily determined by two parameters, that is, the within- and between-flock transmission. The within-flock transmission was assessed fitting experimental data to a logistic growth model and the between-flock transmission was assessed fitting field data to a generalized linear model (GLM), which included three possible infection routes: (1) via an infected flock in the previous cycle, (2) via other infected flocks present on the farm, and (3) from other sources. This model was applied to assess the efficacy of three control scenarios; (1) a ban on other livestock on broiler farms, (2) a ban on thinning, and (3) a reduction of the between-flock transmission. In contrast to the other scenarios, the third one was shown to be most effective. Theoretically, this is accomplished by improved biosecurity. However, the impact of improved biosecurity cannot be specified into specific control measures, and therefore it is not clear what investments are needed. Finally, we also assessed the efficacy of scheduled treatment, that is, fresh meat production solely from test-negative flocks. We found that the reliability of negative test results, which is crucial, strongly depends on the length of time between testing and slaughter. The sensitivity and specificity of the test appeared to be of minor importance.     

Quantitative Risk Assessment of Human Salmonellosis in Canadian Broiler Chicken Breast from Retail to Consumption

The current quantitative risk assessment model followed the framework proposed by the Codex Alimentarius to provide an estimate of the risk of human salmonellosis due to consumption of chicken breasts which were bought from Canadian retail stores and prepared in Canadian domestic kitchens. The model simulated the level of Salmonella contamination on chicken breasts throughout the retail‐to‐table pathway. The model used Canadian input parameter values, where available, to represent risk of salmonellosis. From retail until consumption, changes in the concentration of Salmonella on each chicken breast were modeled using equations for growth and inactivation. The model predicted an average of 318 cases of salmonellosis per 100,000 consumers per year. Potential reasons for this overestimation were discussed. A sensitivity analysis showed that concentration of Salmonella on chicken breasts at retail and food hygienic practices in private kitchens such as cross‐contamination due to not washing cutting boards (or utensils) and hands after handling raw meat along with inadequate cooking contributed most significantly to the risk of human salmonellosis. The outcome from this model emphasizes that responsibility for protection from Salmonella hazard on chicken breasts is a shared responsibility. Data needed for a comprehensive Canadian Salmonella risk assessment were identified for future research.     

Multiobjective optimisation of production,distribution and capacity planning of global supply chains in the process industry

The performance of a supply chain should usually be measured by multiple criteria. We address production, distribution and capacity planning of global supply chains considering cost, responsiveness and customer service level simultaneously. A multiobjective mixed-integer linear programming (MILP) approach is developed with total cost, total flow time and total lost sales as key objectives. Also, two strategies to expand the formulation plants’ capacities are considered in the model. The ε-constraint method and lexicographic minimax method are used as solution approaches to tackle the multiobjective problem. Finally, a numerical example is investigated to demonstrate the applicability of the proposed model and solution approaches.     

Production Competence and Business Strategy: Do They Affect Business Performance?

The purpose of this article is threefold. First, a comprehensive measure of production competence that assesses the level of support that manufacturing provides for the strategic objectives of a firm is developed. Second, hypotheses relating production competence to several financial measures of business performance are tested using data from a large sample of firms (n=65) in the furniture industry. Third, the impact of business strategy both directly on performance and as a moderating variable in relation to production competence is analyzed. The results of the study suggest that production competence may have more of an effect on business performance for certain strategies than for others.     

A Risk Assessment Model for Campylobacter in Broiler Meat

A quantitative microbiological risk assessment model describes the transmission of Campylobacter through the broiler meat production chain and at home, from entering the processing plant until consumption of a chicken breast fillet meal. The exposure model is linked to a dose-response model to allow estimation of the incidence of human campylobacteriosis. The ultimate objective of the model is to serve as a tool to assess the effects of interventions to reduce campylobacteriosis in the Netherlands. The model describes some basic mechanistics of processing, including the nonlinear effects of cross-contamination between carcasses and their leaking feces. Model input is based on the output of an accompanying farm model and Dutch count data of Campylobacters on the birds' exterior and in the feces. When processing data are lacking, expert judgment is used for model parameter estimation. The model shows that to accurately assess of the effects of interventions, numbers of Campylobacter have to be explicitly incorporated in the model in addition to the prevalence of contamination. Also, as count data usually vary by several orders of magnitude, variability in numbers within and especially between flocks has to be accounted for. Flocks with high concentrations of Campylobacter in the feces that leak from the carcasses during industrial processing seem to have a dominant impact on the human incidence. The uncertainty in the final risk estimate is large, due to a large uncertainty at several stages of the chain. Among others, more quantitative count data at several stages of the production chain are needed to decrease this uncertainty. However, this uncertainty is smaller when relative risks of interventions are calculated with the model. Hence, the model can be effectively used by risk management in deciding on strategies to reduce human campylobacteriosis.     

Microbiological and Modeling Approach to Derive Performance Objectives for Bacillus cereus Group in Ready‐to‐Eat Salads

In this article, the performance objectives (POs) for Bacillus cereus group (BC) in celery, cheese, and spelt added as ingredients in a ready‐to‐eat mixed spelt salad, packaged under modified atmosphere, were calculated using a Bayesian approach. In order to derive the POs, BC detection and enumeration were performed in nine lots of naturally contaminated ingredients and final product. Moreover, the impact of specific production steps on the BC contamination was quantified. Finally, a sampling plan to verify the ingredient lots' compliance with each PO value at a 95% confidence level (CL) was defined. To calculate the POs, detection results as well as results above the limit of detection but below the limit of quantification (i.e., censored data) were analyzed. The most probable distribution of the censored data was determined and two‐dimensional (2D) Monte Carlo simulations were performed. The PO values were calculated to meet a food safety objective of 4 log₁₀ cfu of BC for g of spelt salad at the time of consumption. When BC grows during storage between 0.90 and 1.90 log₁₀ cfu/g, the POs for BC in celery, cheese, and spelt ranged between 1.21 log₁₀ cfu/g for celery and 2.45 log₁₀ cfu/g for spelt. This article represents the first attempt to manage the concept of PO and 2D Monte Carlo simulation in the flow chart of a complex food matrix, including raw and cooked ingredients.     

An Exploratory Study of Procurement Strategies for Multi‐Item RFQs in B2B Markets: Antecedents and Impact on Performance

This research explores procurement strategies for multi‐item requests for quotation (RFQs) in business‐to‐business (B2B) markets using responses from 825 purchasing professionals. The study first establishes procurement strategies that differ based on their level of strategic emphasis, i.e., the importance that is placed on the pursuit of four strategic objectives. Underlying objectives, which are obtained via factor analysis, include the focus on price, security of supply, internal procurement efficiencies, and bundle building. Next, cluster analysis is used to derive prototypical strategic approaches. The three cluster groups that emerge possess the same relative ranking of the four objectives, but differ based on the intensity with which these objectives are pursued. The clusters are labelled as the three strategic groups of strategists, opportunists, and responders. The research then explores, using an industrial buyer behavior lens, the impact of environmental antecedents in determining a particular strategy. Environmental variables include purchase importance, market uncertainty, supply base availability, buyer bargaining power, item experience, and supply base experience. Finally, the study tests the impact of procurement strategy on the buyer's perceived performance, suggesting that strategists, placing more emphasis on the pursuit of strategic sourcing objectives, achieve better performance than opportunists and responders.     

A Probabilistic Transmission Model of Salmonella in the Primary Broiler Production Chain

Annual data from the Finnish National Salmonella Control Programme were used to build up a probabilistic transmission model of salmonella in the primary broiler production chain. The data set consisted of information on grandparent, parent, and broiler flock populations. A probabilistic model was developed to describe the unknown true prevalences, vertical and horizontal transmissions, as well as the dynamical model of infections. By combining these with the observed data, the posterior probability distributions of the unknown parameters and variables could be derived. Predictive distributions were derived for the true number of infected broiler flocks under the adopted intervention scheme and these were compared with the predictions under no intervention. With the model, the effect of the intervention used in the programme, i.e., eliminating salmonella positive breeding flocks, could be quantitatively assessed. The 95% probability interval of the posterior predictive distribution for (broiler) flock prevalence under current (1999) situation was [1.3%-17.4%] (no intervention), and [0.9%-5.8%] (with intervention). In the scenario of one infected grandparent flock, these were [2.8%-43.1%] and [1.0%-5.9%], respectively. Computations were performed using WinBUGS and Matlab softwares.     

Quantitative microbiological risk assessment of nontyphoidal Salmonella in ground pork in households in Chengdu,China

Foodborne disease caused by nontyphoidal Salmonella (NTS) is one of the most important food safety issues worldwide. The objectives of this study were to carry out microbial monitoring on the prevalence of NTS in commercial ground pork, investigate consumption patterns, and conduct a quantitative microbiological risk assessment (QMRA) that considers cross-contamination to determine the risk caused by consuming ground pork and ready-to-eat food contaminated during food handling in the kitchen in Chengdu, China. The food pathway of ground pork was simplified and assumed to be several units according to the actual situation and our survey data, which were collected from our research or references and substituted into the QMRA model for simulation. The results showed that the prevalence of NTS in ground pork purchased in Chengdu was 69.64% (95% confidence interval [CI], 60.2–78.0), with a mean contamination level of −0.164 log CFU/g. After general cooking, NTS in ground pork could be eliminated (contamination level of zero). The estimated probability of causing salmonellosis per day was 9.43E-06 (95% CI: 8.82E-06–1.00E-05), while the estimated salmonellosis cases per million people per year were 3442 (95% CI: 3218–3666). According to the sensitivity analysis, the occurrence of cross-contamination was the most important factor affecting the probability of salmonellosis. To reduce the risk of salmonellosis caused by NTS through ground pork consumption, reasonable hygiene prevention and control measures should be adopted during food preparation to reduce cross-contamination. This study provides valuable information for household cooking and food safety management in China.     

Risk of Illness with Salmonella due to Consumption of Raw Unwashed Vegetables Irrigated with Water from the Bogotá River

The Bogotá River receives untreated wastewater from the city of Bogotá and many other towns. Downstream from Bogotá, water from the river is used for irrigation of crops. Concentrations of indicator organisms in the river are high, which is consistent with fecal contamination. To investigate the probability of illness due to exposure to enteric pathogens from the river, specifically Salmonella, we took water samples from the Bogotá River at six sampling locations in an area where untreated water from the river is used for irrigation of lettuce, broccoli, and cabbage. Salmonella concentrations were quantified by direct isolation and qPCR. Concentrations differed, depending on the quantification technique used, ranging between 10^7.7 and 10^9.9 number of copies of gene invA per L and 10^5.3 and 10^8.4 CFU/L, for qPCR and direct isolation, respectively. A quantitative microbial risk assessment model that estimates the daily risk of illness with Salmonella resulting from consuming raw unwashed vegetables irrigated with water from the Bogotá River was constructed using the Salmonella concentration data. The daily probability of illness from eating raw unwashed vegetables ranged between 0.62 and 0.85, 0.64 and 0.86, and 0.64 and 0.85 based on concentrations estimated by qPCR (0.47–0.85, 0.47–0.86, and 0.41–0.85 based on concentrations estimated by direct isolation) for lettuce, cabbage, and broccoli, respectively, which are all above the commonly propounded benchmark of 10^?4 per year. Results obtained in this study highlight the necessity for appropriate wastewater treatment in the region, and emphasize the importance of postharvest practices, such as washing, disinfecting, and cooking.