Quantitative Microbiological Risk Assessment Model Research Articles

Harmonizing Campylobacter risk assessments across European countries – can the pooled process hygiene criteria data be used in the Danish risk assessment model?

This study investigated the possibility of harmonizing quantitative microbiological risk assessment (QMRA) for Campylobacter spp. across European (EU) countries. French Campylobacter data (2020–2021) from neck skin (NS) pools, sampled at slaughterhouses under the European surveillance component for Food Business Operators (FBOs), were adapted to inform a QMRA model that, among others, has been used within the Danish Action Plan against Campylobacter, on the basis of single leg skins (LS) data. Datasets included culture results (in colony forming unit per gram, CFU/g) from 1,284 broiler flocks slaughtered at 13 slaughterhouses representing broiler production in western France. Five pools (of 2–4 NS samples each) per flock were tested. One pool per tested flock was randomly chosen for the analysis. After conducting descriptive statistics (on flock prevalence and meat contaminations across months and years), three contamination transformation factors (CTFs) were estimated to translate NS pools contaminations into single LS contamination, based on data from French and Danish studies. A reference simulation scenario (ScenRef) was set with CTF = 3.2 (i.e. NS pool concentration divided by 3.2); while other 13 scenarios represented an alternative scenario analysis to investigate the impact of: the CTF value (ScenMin with CTF = 2 and ScenMax with CTF = 10), censored test results (ScenUncens) and random choice of pool per flock (ScenSampling-1 to 10), on the risk estimates. The average monthly/annual risk of human disease per poultry meal and the monthly/annual relative risk (RR) of 2021 compared to 2020, were estimated. In ScenRef, the annual RR was 1.22, suggesting an increase of risk of ≈ 22 % in 2021 compared to 2020. The impact of CTFs, censored data and randomized pool sampling per flock, on the annual and (most) monthly RRs, appeared limited. This study gives an overview of the strengths and limitations to be considered for adapting the French FBO data into the Danish model and to harmonize risk assessments across EU countries, accordingly. To reduce uncertainty in risk estimates, it could be considered increasing representativeness of NS tested flock populations and/or using LS rather than NS samples; because LS samples are more representative of actually retailed meat contaminations. If NS pools are maintained, the relationships between concentrations on NS pools and those on consumed meat requires further investigation.

Multipathogen quantitative risk assessment in raw milk soft cheese

We propose a multipathogen Quantitative Microbiological Risk Assessment (QMRA) model to estimate the risk of foodborne illness from bacterial pathogens in raw milk soft cheese. Our work extends an existing QMRA model for pathogenic Shiga toxin-producing Escherichia coli (STEC) (Basak et al.,under review; Perrin et al., 2014) by incorporating the effects of Salmonella and Listeria monocytogenes. This multipathogen model integrates microbial contamination of raw milk at the farm level, as well as the growth and survival of these bacteria during cheese fabrication, ripening, and storage. The public health impact of multipathogen risk associated with raw milk cheese consumption is assessed using Disability-Adjusted Life Years (DALYs). The model evaluates intervention strategies at both pre- and post-harvest stages to estimate intervention costs. Furthermore, it tests various scenarios of these strategies and optimizes intervention parameters to minimize multipathogen risk and associated costs. This article discusses challenges in QMRA model validation, emphasizes model limitations, and explores future perspectives for improvement.

Salmonella Prevalence in Raw Cocoa Beans and a Microbiological Risk Assessment to Evaluate the Impact of Cocoa Liquor Processing on the Reduction of Salmonella

Salmonella in raw cocoa beans (n = 870) from main sourcing areas over nine months was analyzed. It was detected in 71 (ca. 8.2%) samples, with a contamination level of 0.3–46 MPN/g except for one sample (4.1 × 104 CFU/g). Using prevalence and concentration data as input, the impact of thermal treatment in cocoa processing on the risk estimate of acquiring salmonellosis by a random Belgian chocolate consumer was calculated by a quantitative microbiological risk assessment (QMRA) approach. A modular process risk model from raw cocoa beans to cocoa liquor up to a hypothetical final product (70–90% dark chocolate tablet) was set up to understand changes in Salmonella concentrations following the production process. Different thermal treatments during bean or nib steam, nib roasting, or liquor sterilization (achieving a 0–6 log reduction of Salmonella) were simulated. Based on the generic FAO/WHO Salmonella dose–response model and the chocolate consumption data in Belgium, salmonellosis risk per serving and cases per year at population level were estimated. When a 5 log reduction of Salmonella was achieved, the estimated mean risk per serving was 3.35 × 10−8 (95% CI: 3.27 × 10−10–1.59 × 10−7), and estimated salmonellosis cases per year (11.7 million population) was 88 (95% CI: <1–418). The estimated mean risk per serving was 3.35 × 10−9 (95% CI: 3.27 × 10−11–1.59 × 10−8), and the estimated salmonellosis cases per year was 9 (95% CI: <1–42), for a 6 log reduction. The current QMRA model solely considered Salmonella reduction in a single-step thermal treatment in the cocoa process. Inactivation obtained during other process steps (e.g. grinding) might occur but was not considered. As the purpose was to use QMRA as a tool to evaluate the log reduction in the cocoa processing, no postcontamination from the processing environment and ingredients was included. A minimum of 5 log reduction of Salmonella in the single-step thermal treatment of cocoa process was considered to be adequate.

Microbiological Risk Assessment of High-Demand Food from Three Major Cities in Ecuador

The current study was carried out to estimate the risk of disease probability from the consumption of foods such as meats, poultry, unpasteurized cheeses, fruit-based drinks, ready-to-eat fruits, and typical preparations such as Encebollado, ceviche, and Bolón de Verde contaminated with Salmonella, Escherichia coli and Listeria monocytogenes in Ecuador using a quantitative microbiological risk assessment (QMRA). A first-order Monte Carlo simulation probabilistic distribution approach was adopted to assess the occurrence of pathogens in the tested foods. 27 The scenario was simulated using the concentration levels concerning the contaminant and food consumption obtained through an online survey with a sample size of 202 people. A model (100,000 iterations) was run and created in an Excel spreadsheet using @Risk software. The results obtained are the risk of infection (possibilities of becoming infected by eating the food evaluated) and the contaminant dose per portion consumed. Additionally, an exponential model with a single dose was used for risk characterization to determine the probability of becoming ill from contaminated food. The QMRA model performed a prediction for the mean risk of Salmonella infection from ground beef consumption of 1.33 E - 04 log 10 cfu / serving, while the exponential model estimated a value of 1.0 log cfu - serving. In the case of Listeria monocytogenes, the QMRA estimated an average probability of infection in unpasteurized fresh cheese of 5.9E-05 compared to the average disease risk estimated in the risk characterization for L. monocytogenes of 9.50E-13. The QMRA estimated an average risk of infection by E. coli for Encebollado and ceviches of 5.6E -03 compared to the average risk of disease estimated in the risk characterization for Escherichia coli of 0.387 log cfu -ration. These results suggest the need to adopt effective mitigation strategies. Control parameters such as temperature during the supply chain and good hygiene practices during manufacturing can effectively control food-associated pathogens. More data is necessary toimprove the evaluation of the risk developed. Keywords: Microbiological risk análisis, Infectious biological agents (Salmonella, Listeria monocytogenes, Escherichia coli), QMRA (Quantitative Microbial Risk Assessment), Typical foods in Ecuador, Population food consumption in three main cities of Ecuador.

Microbiological Risk Assessment of High-Demand Food from Three Major Cities in Ecuador

The current study was carried out to estimate the risk of disease probability from the consumption of foods such as meats, poultry, unpasteurized cheeses, fruit-based drinks, ready-to-eat fruits, and typical preparations such as Encebollado, ceviche, and Bolón de Verde contaminated with Salmonella, Escherichia coli and Listeria monocytogenes in Ecuador using a quantitative microbiological risk assessment (QMRA). A first-order Monte Carlo simulation probabilistic distribution approach was adopted to assess the occurrence of pathogens in the tested foods. The scenario was simulated using the concentration levels concerning the contaminant and food consumption obtained through an online survey with a sample size of 202 people. A model (100,000 iterations) was run and created in an Excel spreadsheet using @Risk software. The results obtained are the risk of infection (possibilities of becoming infected by eating the food evaluated) and the contaminant dose per portion consumed. Additionally, an exponential model with a single dose was used for risk characterization to determine the probability of becoming ill from contaminated food. The QMRA model performed a prediction for the mean risk of Salmonella infection from ground beef consumption of 1.33 E - 04 log 10 cfu / serving, while the exponential model estimated a value of 1.0 log cfu - serving. In the case of Listeria monocytogenes, the QMRA estimated an average probability of infection in unpasteurized fresh cheese of 5.9E-05 compared to the average disease risk estimated in the risk characterization for L. monocytogenes of 9.50E-13. The QMRA estimated an average risk of infection by E. coli for Encebollado and ceviches of 5.6E -03 compared to the average risk of disease estimated in the risk characterization for Escherichia coli of 0.387 log cfu -ration. These results suggest the need to adopt effective mitigation strategies. Control parameters such as temperature during the supply chain and good hygiene practices during manufacturing can effectively control food-associated pathogens. More data is necessary toimprove the evaluation of the risk developed. Keywords: Microbiological risk análisis, Infectious biological agents (Salmonella, Listeria monocytogenes, Escherichia coli), QMRA (Quantitative Microbial Risk Assessment), Typical foods in Ecuador, Population food consumption in three main cities of Ecuador.

Distribution of SARS-CoV-2 Genomes in Wastewaters and the Associated Potential Infection Risk for Plant Workers in Typical Urban and Peri-Urban Communities of the Buffalo City Region, South Africa.

The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater has been reported in several studies and similar research can be used as a proxy for an early warning of potential Coronavirus disease 2019 (COVID-19) outbreaks. This study focused on profiling the incidence of SARS-CoV-2 genomes in wastewater samples obtained from facilities located in the Buffalo City Municipality. Raw samples were collected weekly using the grab technique for a period of 48 weeks. Ribonucleic acids were extracted from the samples, using the QIAGEN Powersoil Total RNA Extraction kit, and extracted RNA samples were further profiled for the presence of SARS-CoV-2 genomes using Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) technique. Furthermore, various environmental matrices were utilized to estimate the potential health risk to plant operators associated with exposure to SARS-CoV-2 viral particles using the quantitative microbiological risk assessment (QMRA) model. Our findings revealed the prevalence of SARS-CoV-2 genomes with concentrations that ranged from 0.22 × 103 to 17.60 × 103 genome copies per milliliter (GC/mL). Different exposure scenarios were employed for the QMRA model, and the findings indicate a probability of infection (P(i)) ranging from 0.93% to 37.81% across the study sites. Similarly, the P(i) was highly significant (p < 0.001) for the 20 mL volumetric intake as compared to other volumetric intake scenarios, and high P(i) was also observed in spring, autumn, and winter for all WWTPs. The P(i) was significantly different (p < 0.05) with respect to the different seasons and with respect to different volume scenarios.

Improvement of quantitative microbiological risk assessment (QMRA) methodology through integration with gaenetic data.

Quantitative microbiological risk assessment (QMRA) methodology aims to estimate and describe the transmission of pathogenic microorganisms from animals and food to humans. In microbiological literature, the availability of whole genome sequencing (WGS) data is rapidly increasing, and incorporating this data into QMRA has the potential to enhance the reliability of risk estimates. This study provides insight into which are the key pathogen properties for incorporating WGS data to enhance risk estimation, through examination of example risk assessments for important foodborne pathogens: Listeria monocytogenes (Lm), Salmonella, Campylobacter and Shiga toxin-producing Escherichia coli. By investigating the relationship between phenotypic pathogen properties and genetic traits, a better understanding was gained regarding their impact on risk assessment. Virulence of Lm was identified as a promising property for associating different symptoms observed in humans with specific genotypes. Data from a genome-wide association study were used to correlate lineages, serotypes, sequence types, clonal complexes and the presence or absence of virulence genes of each strain with patient's symptoms. We also investigated the effect of incorporating WGS data into a QMRA model including relevant genomic traits of Lm, focusing on the dose-response phase of the risk assessment model, as described with the case/exposure ratio. The results highlighted that WGS studies which include phenotypic information must be encouraged, so as to enhance the accuracy of QMRA models. This study also underscores the importance of executing more risk assessments that consider the ongoing advancements in OMICS technologies, thus allowing for a closer investigation of different bacterial subtypes relevant to human health.

Cross-contamination in the kitchen: A model for quantitative microbiological risk assessment.

A quantitative microbiological risk assessment model for the cross-contamination transmission route in the kitchen (KCC) is presented. Bacteria are transmitted from contaminated (chicken) meat to hands, kitchen utensils, and other surfaces, subsequently contaminating a salad. The model aims to estimate the fraction of bacteria on the meat that is ingested due to cross-contamination, determine the importance of the different transmission routes, and assess the effect of scenarios (interventions) on the fraction ingested. The cross-contamination routes defined, bacterial source-to-recipient transfer fractions as available and derived from literature, and important characteristics (e.g., washing in cold water vs. hot water with soap) shaped the KCC model. With this model, 32 scenarios of an eight-step preparation of a "meat and salad" meal in a domestic kitchen were stochastically simulated. The "cutting board-salad" route proved dominant and the salad plays a major role in the final exposure. A realistic scenario (washing hands, cutting board, and knife with cold water after cutting the meat) estimates that a mean fraction of 3.2E-3 of the bacteria on the meat is ingested. In the case of "hand washing with hot water and soap" and "cutting board and knife replacement," the mean fraction ingested is 3.6E-6. For a subsequent meal, where the contaminated sources were kitchen fomites, the estimated mean fraction is 4.3E-4. In case of hamburger, part of the bacteria is unavailable for cross-contamination, resulting in a mean fraction ingested of about 5.4E-5. The role of the dishcloth in cross-contamination transmission proved to be minor.

Quantitative microbiological risk assessment model for Campylobacter in raw milk of dairy cows in Germany

The consumer demand for raw milk from dairy cows has increased and local sales via vending machines have been intensified. Therefore, this study aimed to assess the risk associated with the consumption of unboiled raw milk contaminated with Campylobacter by estimating the number of campylobacteriosis cases. For this a stochastic quantitative microbial risk assessment (QMRA) model was developed that covered the whole supply chain. Information and data for model parametrization were obtained from research publications. Different probability distributions were used to represent the data whenever possible and probabilistic risk estimation was performed using Monte Carlo simulations. Simulations for outbreaks from single vending machines were performed using the developed QMRA baseline model. Further, different risk mitigation scenarios along the supply chain were evaluated to support risk managers in controlling Campylobacter. The analysis suggest a role for Campylobacter infections due to fecal contamination of cows’ udder. The model can easily be adapted and extended when additional data become available as it is provides in the harmonized exchange Food Safety Knowledge Exchange (FSKX) format.

Risk Reduction Assessment of Vibrio parahaemolyticus on Shrimp by a Chinese Eating Habit

In China, a traditional perspective recommended that consuming seafood should be mixed or matched with vinegar, because people thought this traditional Chinese eating habit could reduce the risk of pathogenic microorganism infection, such as Vibrio parahaemolyticus induced diarrhea. However, this empirical viewpoint has not yet been evaluated scientifically. This study conducted a simplified quantitative microbiological risk assessment (QMRA) model, which was employed to estimate the risk reduction of V. parahaemolyticus on ready-to-eat (RTE) shrimp by consuming with vinegars (white vinegar, aromatic vinegar, or mature vinegar). Results showed the reduction of V. parahaemolyticus density on RTE shrimp after consuming with white vinegar, aromatic vinegar and mature vinegar was respectively 0.9953 log CFU/g (90% confidence interval 0.23 to 1.76), 0.7018 log CFU/g (90% confidence interval 0.3430 to 1.060) and 0.6538 log CFU/g (90% confidence interval 0.346 to 0.9620). The infection risk of V. parahaemolyticus per meal in this QMRA model was quantified by a mean of 0.1250 with the standard deviation of 0.2437. After consuming with white vinegar, aromatic vinegar, and mature vinegar, the mean infection risk of V. parahaemolyticus on shrimp decreased to 0.0478, 0.0652, and 0.0686. The QMRA scenarios indicated significant reductions in infection risk when eating RTE shrimp by the Chinese eating habit (consuming with vinegar). This good eating habit should be recommended to promote the spread of around the world.

Quantitative risk assessment for type A staphylococcal enterotoxin poisoning due to consumption of Minas Frescal cheese in Brazil

This study aimed to estimate the risk of staphylococcal toxin type A (SEA) poisoning from consuming Minas Frescal cheese (MFC) in Brazil. A Quantitative Microbiological Risk Assessment model was developed, focussing on the production of SEA while still in the raw material. The baseline scenario yielded a simulated mean concentration of SEA in the MFC portion of 16.20 ng. The concentration of Staphylococcus aureus in raw milk is proved to be the most influential parameter for the risk, followed by the serving size and the prevalence of toxin genes.

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.

A hierarchical Bayesian quantitative microbiological risk assessment model for Salmonella in the sheep meat food chain

Multiple foodborne routes of Salmonella infection have been observed; however, the majority of the literature to date has been dominated by research into the most frequently observed reservoirs, such as chicken, beef, and pork. While less commonly observed, outbreaks of Salmonella within sheep meat still occur, requiring extensive investigation by food safety inspectors. Risk assessment models inform policy makers and investigators of the risks posed by pathogens at each stage of the food chain, and help suggest at which stages in the food chain outbreaks are likely induced. This work is the first risk assessment into the prevalence of Salmonella throughout the sheep meat food chain, from farm to fork. A Bayesian evidence-synthesis model is used, informed by data gathered from 27 individual studies - an exhaustive search of the existing literature, to express and enumerate the current understanding of Salmonella prevalence in the sheep meat food chain in the form of probabilities of colonisation throughout the food chain. The resulting posterior estimate projects that 9 (0–29 95% HDI) UK individuals are likely to fall ill with salmonellosis due to sheep meat every year. A variance-based sensitivity analysis reveals that the abattoir module is the stage of greatest bacterial proliferation, highlighting it as the most probable source of outbreaks, though not to the exclusion of other factors.

Using Economic Optimization to Derive Site-Specific Treatment Objectives

A procedure to estimate the economically efficient site- or system-specific treatment objective for enteric viruses in drinking water is presented. The health benefits of treatment are estimated using an existing quantitative microbiological risk assessment model for Rotavirus, which yields a reduction in burden of disease, measured in DALYs. The community’s willingness to pay for this reduced disease burden is then inferred using an estimate of the value of an avoided DALY from the literature. Economically efficient treatment occurs where the marginal cost of additional treatment equals the marginal benefit in terms of willingness to pay for avoided illness. In a case study on a small water system, capital and operating costs are estimated for four alternative treatment levels using commercially available UV disinfection systems. The case study results compare the economically efficient virus disinfection level, risk of infection, and burden of disease to international guidelines. A sensitivity analysis suggests that source water quality, population served, and the dose–response model are key inputs. Site-specific treatment objectives offer a viable alternative to prescribed national standards while respecting water safety and local autonomy.

Human campylobacteriosis related to cross-contamination during handling of raw chicken meat: Application of quantitative risk assessment to guide intervention scenarios analysis in the Australian context

Quantitative Microbiological Risk Assessment (QMRA) is a methodology used to organize and analyze scientific information to both estimate the probability and severity of an adverse event as well as prioritize efforts to reduce the risk of foodborne pathogens. No QMRA efforts have been applied to Campylobacter in the Australian chicken meat sector. Hence, we present a QMRA model of human campylobacteriosis related to the occurrence of cross-contamination while handling raw chicken meat in Western Australia (WA). This work fills a gap in Campylobacter risk characterization in Australia and enables benchmarking against risk assessments undertaken in other countries. The model predicted the average probability of the occurrence of illness per serving of salad that became cross-contaminated from being handled following the handling of fresh chicken meat as 7.0 × 10−4 (90% Confidence Interval [CI] ± 4.7 × 10−5). The risk assessment model was utilized to estimate the likely impact of intervention scenarios on the predicted probability of illness (campylobacteriosis) per serving. Predicted relative risk reductions following changes in the retail prevalence of Campylobacter were proportional to the percentage desired in the reduction scenario; a target that is aiming to reduce the current baseline prevalence of Campylobacter in retail chicken by 30% is predicted to yield approximately 30% relative risk reduction. A simulated one-log reduction in the mean concentration of Campylobacter is anticipated to generate approximately 20% relative risk reductions. Relative risk reduction induced by a one-log decrease in the mean was equally achieved when the tail of the input distribution was affected—that is, by a change (one-log reduction) in the standard deviation of the baseline Campylobacter concentration. A scenario assuming a 5% point decrease in baseline probability of cross-contamination at the consumer phase would yield relative risk reductions of 14%, which is as effective as the impact of a strategic target of 10% reduction in the retail prevalence of Campylobacter. In conclusion, the present model simulates the probability of illness predicted for an average individual who consumes salad that has been cross-contaminated with Campylobacter from retail chicken meat in WA. Despite some uncertainties, this is the first attempt to utilize the QMRA approach as a scientific basis to guide risk managers toward implementing strategies to reduce the risk of human campylobacteriosis in an Australian context.

A quantitative risk assessment model for salmonellosis due to milk chocolate consumption in Brazil

This study intended to estimate the probability of salmonellosis in the Brazilian population due to milk chocolate consumption using a quantitative microbiological risk assessment (QMRA). The QMRA model was built to predict the fate of Salmonella through milk chocolate production. The model was divided into three modules: (a) cocoa pre-processing, (b) milk chocolate processing, and (c) milk chocolate consumption and risk characterization, in which was considered the exposure to Salmonella and the risk of illness. Sixteen scenarios were evaluated considering different levels of cocoa seeds contamination (from −2.0 to 1.0 log CFU/g and from −1.4 to 4.0 log CFU/g of Salmonella), different roasting temperature (110 °C and 140 °C) for 15–50 min, cocoa formats (whole-beans or nibs)], and the occurrence of cross-contamination after roasting (from −2.0 to 1.0 log CFU/g of Salmonella. Simulations predicted that consumption of milk chocolate contaminated with Salmonella would result in a mean number of salmonellosis cases/week of 1.3E+05 when the initial concentration of this pathogen ranged from Pert (−2.0 to 1.0 log CFU/g) and nibs were roasted at 140 °C for 15–50 min. On the other hand, when the initial concentration of Salmonella ranged from Pert (−1.4 to 4.0 log CFU/g) and nibs were roasted at 110 °C for 15–50 min; the predictions indicated a mean number of salmonellosis cases/week of 3.2E+07. The simulations also indicated that scenarios in which cross-contamination could occur (in the levels studied) after roasting did not influence the risk of salmonellosis significantly. To the best of our knowledge, this is the first study to evaluate the risk of salmonellosis due to the consumption of milk chocolate in the Brazilian population, which can help risk managers and the chocolate industry to enhance the food safety of this product.

A risk assessment of salmonellosis linked to chicken meals prepared in households of China

A quantitative microbiological risk assessment model was used to quantify the risk of salmonellosis caused by bacterial growth and cross-contamination of chicken meals prepared in households of China. Chinese data on initial loads of Salmonella in chicken carcasses sold at retail, storage time and handling of raw chicken meat in household kitchens and confirmatory transfer rates of Salmonella among different kitchen objects were collected. Only one third of Chinese families in our sample separated the cutting board between raw and ready-to-eat foods. The cross-contamination of ready-to-eat foods from chicken meals via the cutting board, the knife and cooks’ hands increased the frequency of pathogen ingestion and the risk of salmonellosis. A significant decrease in the risk of salmonellosis could be achieved by reducing the cross-contamination when handling raw chicken meat and ready-to-eat foods. Decreasing the prevalence of Salmonella contamination to 8.8% or removing chicken carcasses with contamination densities higher than 100 MPN/100 g at retail was less effective. Using transfer rates of Salmonella from raw chicken meat to the wooden cutting board instead of that from references, a statistically higher risk of salmonellosis per serve due to the cross-contamination in households was observed. The present study validated values of hygiene practices in China to reduce the risk of salmonellosis from contaminated raw chicken meat at retail. Deliberate surveys for cooking behaviors and transfer rates of Salmonella from and to different objects including wooden cutting boards were needed.

A QMRA Model for Salmonella in Pork Products During Preparation and Consumption.

As part of a quantitative microbiological risk assessment (QMRA) food chain model, this article describes a model for the consumer phase for Salmonella-contaminated pork products. Three pork products were chosen as a proxy for the entire pork product spectrum: pork cuts, minced meat patties, and fermented sausages. For pork cuts cross-contamination is considered the most important process and therefore it is modeled in detail. For minced meat, both cross-contamination and undercooking are the relevant processes. For those commodities bacterial growth during transport and storage is also modeled. Fermented sausages are eaten raw and the production may be defective. Variability between consumers' behavior and the impact of variability between production processes at the farm and abattoir are taken into account. Results indicate that Salmonella levels on products may increase significantly during transport and storage. Heating is very efficient at lowering concentrations, yet cross-contamination plays an important role in products that remain contaminated. For fermented sausage it is found that drying is important for Salmonella reduction. Sensitivity analysis revealed that cross- contamination factors "knife cleaning" and "preparation of a salad" are important parameters for pork cuts. For minced meat cleaning of the board, salad consumption, refrigerator temperature, and storage time were significant.

Robustness of a Cross Contamination Model Describing Transfer of Pathogens During Grinding of Meat

This study aimed to evaluate a cross contamination model1 for its capability of describing transfer of Salmonella spp. and L. monocytogenes during grinding of varying sizes and numbers of pieces of meats in two grinder systems. Data from 19 trials were collected. Three evaluation approaches were applied: i) Acceptable Simulation Zone method compared observed with simulated transfer, ii) each trial was fitted and parameters were integrated in a Quantitative Microbiological Risk Assessment model, iii) the Total Transfer Potential was calculated from fitted parameters. Risk estimates revealed that grinding was influenced by sharpness of grinder knife, specific grinder and grinding temperature.

A Bayesian approach to the evaluation of risk-based microbiological criteria for Campylobacter in broiler meat

Shifting from traditional hazard-based food safety management toward risk-based management requires statistical methods for evaluating intermediate targets in food production, such as microbiological criteria (MC), in terms of their effects on human risk of illness. A fully risk-based evaluation of MC involves several uncertainties that are related to both the underlying Quantitative Microbiological Risk Assessment (QMRA) model and the production-specific sample data on the prevalence and concentrations of microbes in production batches. We used Bayesian modeling for statistical inference and evidence synthesis of two sample data sets. Thus, parameter uncertainty was represented by a joint posterior distribution, which we then used to predict the risk and to evaluate the criteria for acceptance of production batches. We also applied the Bayesian model to compare alternative criteria, accounting for the statistical uncertainty of parameters, conditional on the data sets. Comparison of the posterior mean relative risk, $E(\mathit{RR}|\mathrm{data})=E(P(\mathrm{illness}|\mathrm{criterion is met})/P(\mathrm{illness})|\mathrm{data})$, and relative posterior risk, $\mathit{RPR}=P(\mathrm{illness}|\mathrm{data, criterion is met})/P(\mathrm{illness}|\mathrm{data})$, showed very similar results, but computing is more efficient for RPR. Based on the sample data, together with the QMRA model, one could achieve a relative risk of 0.4 by insisting that the default criterion be fulfilled for acceptance of each batch.