Metagenomic analysis of sewage for surveillance of bacterial pathogens: A release experiment to determine sensitivity.

Accurate monitoring of gastro-enteric and other diseases in large populations poses a challenge for public health management. Sewage represents a larger population, is freely obtainable and non-subject to ethical approval. Metagenomic sequencing offers simultaneous, multiple-target analysis. However, no study has demonstrated the sensitivity of metagenomics for detecting bacteria in sewage. In this study, we spot-released 1013 colony-forming units (CFU) of Staphyloccus hyicus (non-pathogenetic strain 842J-88). The strain was flushed down a toilet into the sewer in the catchment area of a public wastewater treatment plant (WWTP), serving a population of 36,000 people. Raw sewage was continuously sampled at the WWTP's inlet over 30- and 60-minute intervals for a total period of seven hours. The experiment was conducted twice with one week in-between release days and under comparable weather conditions. For the metagenomics analyses, the pure single isolate of S. hyicus was sequenced, assembled and added to a large database of bacterial reference sequences. All sewage samples were analyzed by shotgun metagenome sequencing and mapped against the reference database. S. hyicus was identified in duplicate samples at both of two release days and these sequence fragment counts served as a proxy to estimate the minimum number of sick people or sensitivity required in order to observe at least one sick person at 95% probability. We found the sensitivity to be in the range 41-140 and 16-36 sick people at release days 1 and 2, respectively. The WWTP normally serves 36,000 people giving a normalized sensitivity in the range of one in 257 to 2,250 persons.

Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints.

Current surveillance of antimicrobial resistance (AMR) is mostly based on testing indicator bacteria using minimum inhibitory concentration (MIC) panels. Metagenomics has the potential to identify all known antimicrobial resistant genes (ARGs) in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and the subsequent spread to the entire population. To make the simulation realistic, the total cost of the surveillance was constrained, and the sampling schedule was set at one pool per month with 5, 20, 50, or 100 samples. Our simulations demonstrate that a pool of 20-50 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time delay to detection of change of [Formula: see text]15 months in all scenarios. Compared with culture-based surveillance, our simulation indicates that there are neither significant reductions nor increases in time to detect a change using metagenomics. The benefit of metagenomics is that it is possible to monitor all known resistance in one sampling and laboratory procedure in contrast to the current monitoring that is based on the phenotypic characterisation of selected indicator bacterial species. Therefore, overall changes in AMR in a population will be detected earlier using metagenomics due to the fact that the resistance gene does not have to be transferred to and expressed by an indicator bacteria before it is possible to detect.

Global within-species phylogenetics of sewage microbes suggest that local adaptation shapes geographical bacterial clustering.

Most investigations of geographical within-species differences are limited to focusing on a single species. Here, we investigate global differences for multiple bacterial species using a dataset of 757 metagenomics sewage samples from 101 countries worldwide. The within-species variations were determined by performing genome reconstructions, and the analyses were expanded by gene focused approaches. Applying these methods, we recovered 3353 near complete (NC) metagenome assembled genomes (MAGs) encompassing 1439 different MAG species and found that within-species genomic variation was in 36% of the investigated species (12/33) coherent with regional separation. Additionally, we found that variation of organelle genes correlated less with geography compared to metabolic and membrane genes, suggesting that the global differences of these species are caused by regional environmental selection rather than dissemination limitations. From the combination of the large and globally distributed dataset and in-depth analysis, we present a wide investigation of global within-species phylogeny of sewage bacteria. The global differences found here emphasize the need for worldwide data sets when making global conclusions.

Trends in Salmonella Dublin over time in Denmark from food and animal related isolates.

Salmonella enterica serovar Dublin is highly adapted to cattle and a relatively rare cause of human infections. In Denmark S. Dublin has been endemic in the cattle population for many years. A national surveillance program in the cattle population was established at herd-level to reduce the occurrence of S. Dublin. In this study, we analyzed 421 S. Dublin genomes from cattle and food in order to determine the trend of S. Dublin's population size over time in Denmark and the impact of intervention in the cattle industry on the bacterial population size. A phylogenetic tree based on SNPs exhibited two major clades and one small cluster. All isolates were ST10. The temporal phylogenetic tree for the S. Dublin isolates showed that the most recent common ancestor was estimated to be in ∼1980 for the two major clades. An effective population size over time based on a Bayesian skyline plot showed that the population size of S. Dublin decreased significantly between 2014 and 2019 in both major clades. This result was concordant with the decrease of infected human cases by S. Dublin in Denmark. The strengthening of a surveillance program in Denmark could be the cause for the reduction of S. Dublin's effective population size. This study showed that whole genome sequencing combined with computer intensive phylogenetic analysis estimating the effective size of the S. Dublin's population over time is a strongly relevant measure with respect to assessing the impact of control measures aiming to reduce the bacterial population in the reservoir and the risk for human infection.

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.

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.

System Mapping of Antimicrobial Resistance to Combat a Rising Global Health Crisis.

Antimicrobial resistance (AMR) decreases the effectiveness of antimicrobials to treat bacterial infections in humans and animals. The increased occurrence of AMR in bacterial population in humans, animals, and the environment requires the measures to combat a rising global health crisis. The aim of this research was to present current knowledge on AMR in a system map and to identify potential explanations of former identified variables significantly associated with AMR. This study applies a systems thinking approach and uses feedback loops to visualize the interconnections between human, animal, and environmental components in a circular AMR system map model. First, a literature review focusing on AMR and socioeconomic factors, wicked problem, and system change was carried out, which was then processed in a system map to conceptualize the present core challenges of AMR via feedback loops. Second, to investigate possible underlying values of the society and those that influence humans' behavior in the present AMR system, an iceberg model was established. Third, leverage points were assessed to estimate which kinds of interventions would have the greatest effect to mitigate AMR in the system. The present AMR system map implies the potential to identify and visualize important risk factors that are direct or indirect drivers of AMR. Our results show that the tool of system mapping, which interconnects animals, humans, and environment in one model, can approach AMR holistically and be used to assess potential powerful entry points for system wide interventions. This study shows that system maps are beneficial as a model to predict the relative effect of different interventions and adapt to rapidly changing environments in a complex world. Systems thinking is considered as a complementing approach to the statistical thinking, and further research is needed to evaluate the use of such tools for the development and monitoring of interventions.

Risk of consuming products with or without precautionary wheat or gluten labelling for persons with coeliac disease.

Persons with Coeliac disease (CD) need to keep a lifelong diet without gluten and therefore need to know which foods are safe to eat. The objective of this study was to analyse ordinary foods products without gluten containing ingredients (PWG) with or without the precautionary allergen statement (PAL) "May contain wheat/gluten" or similar wording and use these data to perform a probabilistic risk assessment. Foods with and without PAL were analysed for gluten. Inputs for the risk assessment were analytical results, daily food consumption and data from a 90-days challenge study in coeliac patients (Catassi et al., 2007).20/77 products with PAL and 10/51 without PAL had gluten ≥5 mg/kg 3/77 with PAL and 3/51 without PAL had gluten ≥20 mg/kg. A coconut cookie brand was outlier with 421 mg gluten/kg. The likelihood of developing mucosal damage in the CD population when eating the same PWG for 90 days in addition to certified gluten-free products was low (0.2-3.2%) with little difference between with or without PAL. Including the coconut cookie results increased the risk to 3.8-9.2%. Caution should be taken in connection to foods where there is an obvious chance of contamination.

Robustness in quantifying the abundance of antimicrobial resistance genes in pooled faeces samples from batches of slaughter pigs using metagenomics analysis.

OBJECTIVES: With the continued spread of antimicrobial resistance (AMR) in animals, it is important to assess its occurrence throughout a microbiome quantitatively in order to evaluate significantly affecting factors, e.g. antimicrobial usage. Metagenomics methods make it possible to measure the abundance of AMR genes in complex samples such as pooled faeces samples from batches of slaughter pigs. This study was performed to determine the random error in pooled samples from batches of pigs at slaughter and the measurement error from the metagenomics processes. METHODS: In four farms, two pooled samples were obtained from a batch of slaughter pigs by two individual samplers, and each pooled sample was thereafter processed twice. Hierarchically clustered heatmaps were applied to evaluate dissimilarities between samples. The coefficient of variation was used to calculate the percentage difference between samples from the same farm. RESULTS: Results of the analysis revealed that it was not possible to quantitatively separate the variation arising from sampling and metagenomics processes. They both contributed to the overall measurement error in batches of slaughter pigs. CONCLUSION: Sampling of single pigs in 30 randomly selected pig pens within the farms provides a composition representative for frequently occurring AMR genes present within the farms, while rare genes were not dispersed in a similar manner. Aggregating the resistance abundance at gene family or antimicrobial class level will reduce the apparent variation originating from errors in sampling and metagenomics processing.

Using stochastic dynamic modelling to estimate the sensitivity of current and alternative surveillance program of Salmonella in conventional broiler production.

Since 2018, the EU commission has declared the Danish broiler industry to be Salmonella free. However, there is continuous Salmonella pressure from the environment, and a number of parent flocks and broiler flocks become infected annually. When a parent flock becomes infected, the infection can be transmitted vertically to the broiler flocks, before the parent flock is detected and destroyed, including the eggs at the hatchery. To address this issue, we developed stochastic dynamic modelling of transmission of Salmonella in parent flocks and combined that with the relation between flock prevalence and test sensitivity for environmental samples in the flock. Results suggested that after 10 and 100 infected hens were seeded, the likelihood of detecting an infected parent flock within the three first weeks after the infection was strongly influenced by the taking of five boot swabs (95% CI 70-100) instead of two (95% CI 40-100) or the supplementing of the two boot swabs by a dust sample (95% CI 43-100). Results suggest that the likelihood of detecting the broiler flock as infected in the program was estimated to at least 99% in broiler flock even if only one chicken was initially infected. These findings are of relevance for managing parent flocks and eggs at the hatchery in case of Salmonella infection in parent flocks in the Danish poultry.

Inactivation of hepatitis A virus and murine norovirus on surfaces of plastic, steel and raspberries using steam-ultrasound treatment.

The leading causes of foodborne viral disease outbreaks are human norovirus and hepatitis A virus (HAV). Their environmental persistence enables contamination of kitchen surfaces and crops often consumed raw, such as berries. Many decontamination procedures are inefficient and unsuitable for surfaces of industrial kitchen environments and soft fruits. In this study, we investigated the efficiency of a novel surface decontamination technology, combining steam and ultrasound (steam-ultrasound). Plastic, steel or raspberry surfaces were spiked with the norovirus surrogate, murine norovirus (MNV), and HAV, and steam-ultrasound treated at 85, 90 and 95 °C for 0-5 s. Post treatment viruses were titrated for survival by plaque assay and for genome stability by real-time quantitative PCR (RT-qPCR) of nucleic acid extracts. Survival of viruses were estimated in a log-linear model and the treatment time requirements for each decimal reduction (D value) in viral survival were calculated. The estimated D values of MNV or HAV were 0.4-0.2 or 1.1-0.8 s on plastic, 0.9-0.7 or 1.4-0.8 s on steel and 1.6-1.7 or 3.2-4.7 s on raspberries. No clear trend of genome reduction was observed with tested treatment parameters. Raspberries treated up to 4 s retained its natural texture and visual appeal similar to untreated controls whilst monitored for 7 days. In conclusion, steam-ultrasound treatment can within seconds reduce the titre of foodborne viruses on surfaces of plastic, steel and raspberries. This may particularly benefit industrial scale production of soft fruits for raw consumption and for swift non-hazardous decontamination of industrial kitchen surfaces.

Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage.

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.

Proficiency of WHO Global Foodborne Infections Network External Quality Assurance System Participants in Identification and Susceptibility Testing of Thermotolerant Campylobacter spp. from 2003 to 2012.

Campylobacter spp. are foodborne and waterborne pathogens. While rather accurate estimates for these pathogens are available in industrialized countries, a lack of diagnostic capacity in developing countries limits accurate assessments of prevalence in many regions. Proficiency in the identification and susceptibility testing of these organisms is critical for surveillance and control efforts. The aim of the study was to assess performance for identification and susceptibility testing of thermotolerant Campylobacter spp. among laboratories participating in the World Health Organization (WHO) Global Foodborne Infections Network (GFN) External Quality Assurance System (EQAS) over a 9-year period. Participants (primarily national-level laboratories) were encouraged to self-evaluate their performance as part of continuous quality improvement. The ability to correctly identify Campylobacter spp. varied by year and ranged from 61.9% (2008) to 90.7% (2012), and the ability to correctly perform antimicrobial susceptibility testing (AST) for Campylobacter spp. appeared to steadily increase from 91.4% to 93.6% in the test period (2009 to 2012). The poorest performance (60.0% correct identification and 86.8% correct AST results) was observed in African laboratories. Overall, approximately 10% of laboratories reported either an incorrect identification or antibiogram. As most participants were supranational reference laboratories, these data raise significant concerns regarding capacity and proficiency at the local clinical level. Addressing these diagnostic challenges is critical for both patient-level management and broader surveillance and control efforts.

Author Correction: Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries.

In the version of this Article originally published, the surname of author Oksana Lukjancenko was spelt incorrectly as 'Lukjacenko'. This has now been corrected.

Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries.

Antimicrobial resistance (AMR) in bacteria and associated human morbidity and mortality is increasing. The use of antimicrobials in livestock selects for AMR that can subsequently be transferred to humans. This flow of AMR between reservoirs demands surveillance in livestock and in humans. We quantified and characterized the acquired resistance gene pools (resistomes) of 181 pig and 178 poultry farms from nine European countries, sequencing more than 5,000 Gb of DNA using shotgun metagenomics. We quantified acquired AMR using the ResFinder database and a second database constructed for this study, consisting of AMR genes identified through screening environmental DNA. The pig and poultry resistomes were very different in abundance and composition. There was a significant country effect on the resistomes, more so in pigs than in poultry. We found higher AMR loads in pigs, whereas poultry resistomes were more diverse. We detected several recently described, critical AMR genes, including mcr-1 and optrA, the abundance of which differed both between host species and between countries. We found that the total acquired AMR level was associated with the overall country-specific antimicrobial usage in livestock and that countries with comparable usage patterns had similar resistomes. However, functionally determined AMR genes were not associated with total drug use.

Computional algorithm for lifetime exposure to antimicrobials in pigs using register data-The LEA algorithm.

Accurate and detailed data on antimicrobial exposure in pig production are essential when studying the association between antimicrobial exposure and antimicrobial resistance. Due to difficulties in obtaining primary data on antimicrobial exposure in a large number of farms, there is a need for a robust and valid method to estimate the exposure using register data. An approach that estimates the antimicrobial exposure in every rearing period during the lifetime of a pig using register data was developed into a computational algorithm. In this approach data from national registers on antimicrobial purchases, movements of pigs and farm demographics registered at farm level are used. The algorithm traces batches of pigs retrospectively from slaughter to the farm(s) that housed the pigs during their finisher, weaner, and piglet period. Subsequently, the algorithm estimates the antimicrobial exposure as the number of Animal Defined Daily Doses for treatment of one kg pig in each of the rearing periods. Thus, the antimicrobial purchase data at farm level are translated into antimicrobial exposure estimates at batch level. A batch of pigs is defined here as pigs sent to slaughter at the same day from the same farm. In this study we present, validate, and optimise a computational algorithm that calculate the lifetime exposure of antimicrobials for slaughter pigs. The algorithm was evaluated by comparing the computed estimates to data on antimicrobial usage from farm records in 15 farm units. We found a good positive correlation between the two estimates. The algorithm was run for Danish slaughter pigs sent to slaughter in January to March 2015 from farms with more than 200 finishers to estimate the proportion of farms that it was applicable for. In the final process, the algorithm was successfully run for batches of pigs originating from 3026 farms with finisher units (77% of the initial population). This number can be increased if more accurate register data can be obtained. The algorithm provides a systematic and repeatable approach to estimating the antimicrobial exposure throughout the rearing period, independent of rearing site for finisher batches, as a lifetime exposure measurement.

A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds.

OBJECTIVES: Reliable methods for monitoring antimicrobial resistance (AMR) in livestock and other reservoirs are essential to understand the trends, transmission and importance of agricultural resistance. Quantification of AMR is mostly done using culture-based techniques, but metagenomic read mapping shows promise for quantitative resistance monitoring. METHODS: We evaluated the ability of: (i) MIC determination for Escherichia coli; (ii) cfu counting of E. coli; (iii) cfu counting of aerobic bacteria; and (iv) metagenomic shotgun sequencing to predict expected tetracycline resistance based on known antimicrobial consumption in 10 Danish integrated slaughter pig herds. In addition, we evaluated whether fresh or manure floor samples constitute suitable proxies for intestinal sampling, using cfu counting, qPCR and metagenomic shotgun sequencing. RESULTS: Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on antimicrobial consumption. Our metagenomic approach had sufficient resolution to detect antimicrobial-induced changes to individual resistance gene abundances. Pen floor manure samples were found to represent rectal samples well when analysed using metagenomics, as they contain the same DNA with the exception of a few contaminating taxa that proliferate in the extraintestinal environment. CONCLUSIONS: We present a workflow, from sampling to interpretation, showing how resistance monitoring can be carried out in swine herds using a metagenomic approach. We propose metagenomic sequencing should be part of routine livestock resistance monitoring programmes and potentially of integrated One Health monitoring in all reservoirs.

The policy implications of urban open space commercial vegetable farmers' willingness and ability to pay for reclaimed water for irrigation in Kumasi, Ghana.

The acute waste management problems, coupled with the proliferation of small scale industries in many developing countries, make low quality water treatment before use inevitable in the long run. These industries have the potential to discharge effluent containing chemicals and heavy metals into the environment. The indiscriminative use of pharmaceutical products by households in many of these countries is another source of health concern. Low quality water treatment in these countries has however been hampered by the high cost of infrastructure provision and maintenance. Cost-sharing among stakeholders appears to be a promising strategy to finance and maintain the wastewater treatment infrastructure. In this study therefore, the willingness and ability of urban open space commercial vegetable farmers to pay for reclaimed water for irrigation purposes has been assessed. One hundred open space commercial vegetable farmers and four vegetable farmers' associations were selected and interviewed in Kumasi in Ghana using semi-structured interview schedules and interview guides respectively. The results of the study show that approximately three out of every five vegetable farmers were willing to pay for reclaimed water for irrigation. The results further show that the probability of being willing to pay by farmers who agreed that the current water they used for irrigation was harmful is approximately 5.3 times greater than that of those who did not. The analysis of the farmers' ability to pay revealed that all the farmers would be capable of paying for reclaimed water at a price of US$0.11/m(3). This has implications for land tenure security and vegetable consumers' willingness to pay higher prices for the produce.

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.

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.