Quantifying health risks from ESBL-producing Escherichia coli in Dutch broiler production chains and potential interventions using compartmental models.

Extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (E. coli) in animals are considered a human health threat, because this type of bacteria can serve as a reservoir of antibiotic resistant genes and act as a continuous threat of the emergence of new resistant bacteria, in addition to the direct effect of making infection untreatable. Although the prevalence of ESBL producing bacteria in broilers was drastically reduced in the Netherlands, chicken meat still has the highest prevalence among meat products. Therefore, further control of the ESBL-producing E. coli in the broiler production chain is important to reduce public health risks. The main objectives of this study were to evaluate the effectiveness of intervention scenarios to reduce the transmission of ESBL-producing E. coli in the broiler production chain and to quantitatively estimate the risk to public health. In this study, we developed two different types of transmission models that described the observed time-related decline in prevalence during a production round: one with time-dependent decline in susceptibility and one with partial immunity to phylogenetic groups. Both models incorporated the environmental contamination effect between production rounds and within flocks. The parameter values, including transmission rate and recovery rate, were estimated by Approximate Bayesian computation (ABC) method using data from a longitudinal study in a Dutch organic broiler farm. We applied the models to the three production stages in the broiler production chain, beginning from the Parent Stock (PS) farms, the hatcheries, and to the broiler farms. In our models, eggs were collected from different parent stock farms and transported to the hatchery and from there to a broiler farm.The size of a flock and the number of farms were adjusted to the Dutch situation. Both models were able to describe the observed dynamics within and between the production stages equally well, with estimated ESBL-producing E. coli prevalence of 8.98% and 11.47% in broilers at slaughter and 0.12% and 0.15% in humans due to chicken consumption. Both models indicated that improving farm management to eliminate the bacteria from the environment was the most effective intervention, making this outcome robust. Although chicken meat consumption is not a major risk factor for human carriage of the bacteria according to our models, reducing the bacteria in the PS and broiler farm environment to at least one percent can further decrease the prevalence in humans.

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.

A statistical modelling approach for source attribution meta-analysis of sporadic infection with foodborne pathogens.

Numerous source attribution studies for foodborne pathogens based on epidemiological and microbiological methods are available. These studies provide empirical data for modelling frameworks that synthetize the quantitative evidence at our disposal and reduce reliance on expert elicitations. Here, we develop a statistical model within a Bayesian estimation framework to integrate attribution estimates from expert elicitations with estimates from microbial subtyping and case-control studies for sporadic infections with four major bacterial zoonotic pathogens in the Netherlands (Campylobacter, Salmonella, Shiga toxin-producing E. coli [STEC] O157 and Listeria). For each pathogen, we pooled the published fractions of human cases attributable to each animal reservoir from the microbial subtyping studies, accounting for the uncertainty arising from the different typing methods, attribution models, and year(s) of data collection. We then combined the population attributable fractions (PAFs) from the case-control studies according to five transmission pathways (domestic food, environment, direct animal contact, human-human transmission and travel) and 11 groups within the foodborne pathway (beef/lamb, pork, poultry meat, eggs, dairy, fish/shellfish, fruit/vegetables, beverages, grains, composite foods and food handlers/vermin). The attribution estimates were biologically plausible, allowing the human cases to be attributed in several ways according to reservoirs, transmission pathways and food groups. All pathogens were predominantly foodborne, with Campylobacter being mostly attributable to the chicken reservoir, Salmonella to pigs (albeit closely followed by layers), and Listeria and STEC O157 to cattle. Food-wise, the attributions reflected those at the reservoir level in terms of ranking. We provided a modelling solution to reach consensus attribution estimates reflecting the empirical evidence in the literature that is particularly useful for policy-making and is extensible to other pathogens and domains.

Modelling and magnitude estimation of cross-contamination in the kitchen for quantitative microbiological risk assessment (QMRA).

In the kitchen of the consumer, two main transmission routes are relevant for quantitative microbiological risk assessment (QMRA): the cross-contamination route, where a pathogen on a food product may evade heating by transmission via hands, kitchen utensils and other surfaces, e.g. to non-contaminated products to be consumed raw; and the heating route, where pathogens remain on the food product and are for the most part inactivated through heating. This project was undertaken to model and estimate the magnitude of cross-contamination in the domestic environment. Scientific information from the relevant literature was collected and analyzed, to define the cross-contamination routes, to describe the variability sources and to extract and harmonise the transfer fractions to be included as model parameters. The model was used to estimate the relative impact of the cross-contamination routes for different scenarios. In addition, the effectiveness of several interventions in reducing the risk of food-borne diseases due to cross-contamination was investigated. The outputs of the model showed that the cutting board route presents a higher impact compared to other routes and replacement of the kitchen utensils is more effective than other interventions investigated; the transfer to other surfaces and objects, which can house bacteria in the environment, is also described. Laboratory cross-contamination trials have been performed to estimate bacterial transfer via cutting, from the external surface of the meat to the cutting surfaces and to the knife. The results, obtained from the laboratory trials, show magnitudes of and differences in the bacterial transfer fraction to the knife and the cutting surface in relation to which side of the meat is contaminated. Despite the complexity of factors which influence bacterial transfer, the combination of laboratory work with mathematical modelling enhanced scientific understanding and appreciation of the uncertainty of the estimates. QMRA methodology results in magnitude estimation of cross-contamination in the kitchen and evaluation of intervention strategies.

Attributable sources of community-acquired carriage of Escherichia coli containing ß-lactam antibiotic resistance genes: a population-based modelling study.

BACKGROUND: Extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-EC), plasmid-mediated AmpC-producing E coli (pAmpC-EC), and other bacteria are resistant to important ß-lactam antibiotics. ESBL-EC and pAmpC-EC are increasingly reported in animals, food, the environment, and community-acquired and health-care-associated human infections. These infections are usually preceded by asymptomatic carriage, for which attributions to animal, food, environmental, and human sources remain unquantified. METHODS: In this population-based modelling study, we collected ESBL and pAmpC gene data on the Netherlands population for 2005-17 from published datasets of gene occurrences in E coli isolates from different sources, and from partners of the ESBL Attribution Consortium and the Dutch National Antimicrobial Surveillance System. Using these data, we applied an established source attribution model based on ESBL-EC and pAmpC-EC prevalence and gene data for humans, including high-risk populations (ie, returning travellers, clinical patients, farmers), farm and companion animals, food, surface freshwater, and wild birds, and human exposure data, to quantify the overall and gene-specific attributable sources of community-acquired ESBL-EC and pAmpC-EC intestinal carriage. We also used a simple transmission model to determine the basic reproduction number (R0) in the open community. FINDINGS: We identified 1220 occurrences of ESBL-EC and pAmpC-EC genes in humans, of which 478 were in clinical patients, 454 were from asymptomatic carriers in the open community, 103 were in poultry and pig farmers, and 185 were in people who had travelled out of the region. We also identified 6275 occurrences in non-human sources, including 479 in companion animals, 4026 in farm animals, 66 in wild birds, 1430 from food products, and 274 from surface freshwater. Most community-acquired ESBL-EC and pAmpC-EC carriage was attributed to human-to-human transmission within or between households in the open community (60·1%, 95% credible interval 40·0-73·5), and to secondary transmission from high-risk groups (6·9%, 4·1-9·2). Food accounted for 18·9% (7·0-38·3) of carriage, companion animals for 7·9% (1·4-19·9), farm animals (non-occupational contact) for 3·6% (0·6-9·9), and swimming in freshwater and wild birds (ie, environmental contact) for 2·6% (0·2-8·7). We derived an R0 of 0·63 (95% CI 0·42-0·77) for intracommunity transmission. INTERPRETATION: Although humans are the main source of community-acquired ESBL-EC and pAmpC-EC carriage, the attributable non-human sources underpin the need for longitudinal studies and continuous monitoring, because intracommunity ESBL-EC and pAmpC-EC spread alone is unlikely to be self-maintaining without transmission to and from non-human sources. FUNDING: 1Health4Food, Dutch Ministry of Economic Affairs, and the EU's Horizon-2020 through One-Health European Joint Programme.

Correction: Time to acquire and lose carriership of ESBL/pAmpC producing E. coli in humans in the Netherlands.

[This corrects the article DOI: 10.1371/journal.pone.0193834.].

Time to acquire and lose carriership of ESBL/pAmpC producing E. coli in humans in the Netherlands.

A subset of the study population from a cross-sectional study of carriership of ESBL/pAmpC-producing E. coli (ESBL-E) in the general population was followed up by five successive samples over an approximate half year period, leading to six samples in 333 persons. Fecal samples were cultured and analyzed for the presence of E. coli types as characterized by MLST, and ESBL/pAmpC genes were analysed by PCR and sequencing. The study included 255 persons who had a negative first sample, to allow observations of acquiring carriership of ESBL-E. Any individual record thus consisted of a series of snapshots of episodes of presence and absence of ESBL-E carriage. A survival model was built to estimate times to acquire or lose carriership, allowing for any combination of ESBL/pAmpC gene and E. coli MLST type. In carriers, the mean time to lose carriership was 1.1 (95% range 0.8-1.6) years. The estimated mean time to acquire carriership was 3.0 (95% range 1.6-6.3) years. Analysis of these times by ESBL/pAmpC gene found substantial variation among resistance genes both in persistence of carriership and in rates of acquiring carriership: blaCTX-M-1, blaCTX-M-14, blaCTX-M-15, blaCTX-M-27 and blaSHV-12 were easily acquired, but blaCTX-M-1 and blaSHV-12 were also easily lost, while blaCTX-M-15, blaCTX-M-27 and blaCMY-2 were more likely to persist. When in addition bacterial host types were included, some combinations appeared more persistent than others (blaCTX-M-1 in ST10 and ST58; blaCTX-M-14, blaCMY-2, and blaSHV-12 in ST69), or were acquired with higher frequency (blaCTX-M-14 in ST38, ST69, and ST131; blaCTX-M-15 and blaCTX-M-27 in ST131; blaSHV-12 in ST69). The relatively short duration of carriership means that when an intervention drastically reduces the exposure of humans to ESBL-E, the prevalence will be halved in 0.66 years. The observed differences between carriage rates of ESBL/pAmpC genes and E. coli strains need further investigation.

Comparative Exposure Assessment of ESBL-Producing Escherichia coli through Meat Consumption.

The presence of extended-spectrum ß-lactamase (ESBL) and plasmidic AmpC (pAmpC) producing Escherichia coli (EEC) in food animals, especially broilers, has become a major public health concern. The aim of the present study was to quantify the EEC exposure of humans in The Netherlands through the consumption of meat from different food animals. Calculations were done with a simplified Quantitative Microbiological Risk Assessment (QMRA) model. The model took the effect of pre-retail processing, storage at the consumers home and preparation in the kitchen (cross-contamination and heating) on EEC numbers on/in the raw meat products into account. The contribution of beef products (78%) to the total EEC exposure of the Dutch population through the consumption of meat was much higher than for chicken (18%), pork (4.5%), veal (0.1%) and lamb (0%). After slaughter, chicken meat accounted for 97% of total EEC load on meat, but chicken meat experienced a relatively large effect of heating during food preparation. Exposure via consumption of filet americain (a minced beef product consumed raw) was predicted to be highest (61% of total EEC exposure), followed by chicken fillet (13%). It was estimated that only 18% of EEC exposure occurred via cross-contamination during preparation in the kitchen, which was the only route by which EEC survived for surface-contaminated products. Sensitivity analysis showed that model output is not sensitive for most parameters. However, EEC concentration on meat other than chicken meat was an important data gap. In conclusion, the model assessed that consumption of beef products led to a higher exposure to EEC than chicken products, although the prevalence of EEC on raw chicken meat was much higher than on beef. The (relative) risk of this exposure for public health is yet unknown given the lack of a modelling framework and of exposure studies for other potential transmission routes.

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.

Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence.

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose-infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion.

Public Health Relevance of Cross-Contamination in the Fresh-Cut Vegetable Industry.

Although quantitative studies have revealed that cross-contamination during the washing stage of fresh produce occurs, the importance of cross-contamination in terms of public health relevance has rarely been assessed. The direct distribution of initially contaminated leafy vegetables to a multitude of servings by cutting and mixing also has not been addressed. The goal of this study was to assess the attribution of both contamination pathways to disease risk. We constructed a transparent and exploratory mathematical model that simulates the dispersion of contamination from a load of leafy greens during industrial washing. The risk of disease was subsequently calculated using a Beta-Poisson dose-response relation. The results indicate that up to contamination loads of 10(6) CFU the direct contamination route is more important than the indirect route (i.e., cross-contamination) in terms of number of illnesses. We highlight that the relevance of cross-contamination decreases with more diffuse and uniform contamination, and we infer that prevention of contamination in the field is the most important risk management strategy and that disinfection of washing water can be an additional intervention to tackle potentially high (>10(6) CFU) point contamination levels.

A QMRA for the Transmission of ESBL-Producing Escherichia coli and Campylobacter from Poultry Farms to Humans Through Flies.

The public health significance of transmission of ESBL-producing Escherichia coli and Campylobacter from poultry farms to humans through flies was investigated using a worst-case risk model. Human exposure was modeled by the fraction of contaminated flies, the number of specific bacteria per fly, the number of flies leaving the poultry farm, and the number of positive poultry houses in the Netherlands. Simplified risk calculations for transmission through consumption of chicken fillet were used for comparison, in terms of the number of human exposures, the total human exposure, and, for Campylobacter only, the number of human cases of illness. Comparing estimates of the worst-case risk of transmission through flies with estimates of the real risk of chicken fillet consumption, the number of human exposures to ESBL-producing E. coli was higher for chicken fillet as compared with flies, but the total level of exposure was higher for flies. For Campylobacter, risk values were nearly consistently higher for transmission through flies than for chicken fillet consumption. This indicates that the public health risk of transmission of both ESBL-producing E. coli and Campylobacter to humans through flies might be of importance. It justifies further modeling of transmission through flies for which additional data (fly emigration, human exposure) are required. Similar analyses of other environmental transmission routes from poultry farms are suggested to precede further investigations into flies.

A quantitative microbiological risk assessment for Campylobacter in petting zoos.

The significance of petting zoos for transmission of Campylobacter to humans and the effect of interventions were estimated. A stochastic QMRA model simulating a child or adult visiting a Dutch petting zoo was built. The model describes the transmission of Campylobacter in animal feces from the various animal species, fences, and the playground to ingestion by visitors through touching these so-called carriers and subsequently touching their lips. Extensive field and laboratory research was done to fulfill data needs. Fecal contamination on all carriers was measured by swabbing in 10 petting zoos, using Escherichia coli as an indicator. Carrier-hand and hand-lip touching frequencies were estimated by, in total, 13 days of observations of visitors by two observers at two petting zoos. The transmission from carrier to hand and from hand to lip by touching was measured using preapplied cow feces to which E. coli WG5 was added as an indicator. Via a Beta-Poisson dose-response function, the number of Campylobacter cases for the whole of the Netherlands (16 million population) in a year was estimated at 187 and 52 for children and adults, respectively, so 239 in total. This is significantly lower than previous QMRA results on chicken fillet and drinking water consumption. Scenarios of 90% reduction of the contamination (meant to mimic cleaning) of all fences and just goat fences reduces the number of cases by 82% and 75%, respectively. The model can easily be adapted for other fecally transmitted pathogens.

Uncertainty of population risk estimates for pathogens based on QMRA or epidemiology: a case study of Campylobacter in the Netherlands.

Epidemiology and quantitative microbiological risk assessment are disciplines in which the same public health measures are estimated, but results differ frequently. If large, these differences can confuse public health policymakers. This article aims to identify uncertainty sources that explain apparent differences in estimates for Campylobacter spp. incidence and attribution in the Netherlands, based on four previous studies (two for each discipline). An uncertainty typology was used to identify uncertainty sources and the NUSAP method was applied to characterize the uncertainty and its influence on estimates. Model outcomes were subsequently calculated for alternative scenarios that simulated very different but realistic alternatives in parameter estimates, modeling, data handling, or analysis to obtain impressions of the total uncertainty. For the epidemiological assessment, 32 uncertainty sources were identified and for QMRA 67. Definitions (e.g., of a case) and study boundaries (e.g., of the studied pathogen) were identified as important drivers for the differences between the estimates of the original studies. The range in alternatively calculated estimates usually overlapped between disciplines, showing that proper appreciation of uncertainty can explain apparent differences between the initial estimates from both disciplines. Uncertainty was not estimated in the original QMRA studies and underestimated in the epidemiological studies. We advise to give appropriate attention to uncertainty in QMRA and epidemiological studies, even if only qualitatively, so that scientists and policymakers can interpret reported outcomes more correctly. Ideally, both disciplines are joined by merging their strong respective properties, leading to unified public health measures.

A quantitative microbial risk assessment for meatborne Toxoplasma gondii infection in The Netherlands.

Toxoplasma gondii is an important foodborne pathogen, and the cause of a high disease burden due to congenital toxoplasmosis in The Netherlands. The aim of this study was to quantify the relative contribution of sheep, beef and pork products to human T. gondii infections by Quantitative Microbial Risk Assessment (QMRA). Bradyzoite concentration and portion size data were used to estimate the bradyzoite number in infected unprocessed portions for human consumption. The reduction factors for salting, freezing and heating as estimated based on published experiments in mice, were subsequently used to estimate the bradyzoite number in processed portions. A dose-response relation for T. gondii infection in mice was used to estimate the human probability of infection due to consumption of these originally infected processed portions. By multiplying these probabilities with the prevalence of T. gondii per livestock species and the number of portions consumed per year, the number of infections per year was calculated for the susceptible Dutch population and the subpopulation of susceptible pregnant women. QMRA results predict high numbers of infections per year with beef as the most important source. Although many uncertainties were present in the data and the number of congenital infections predicted by the model was almost twenty times higher than the number estimated based on the incidence in newborns, the usefulness of the advice to thoroughly heat meat is confirmed by our results. Forty percent of all predicted infections is due to the consumption of unheated meat products, and sensitivity analysis indicates that heating temperature has the strongest influence on the predicted number of infections. The results also demonstrate that, even with a low prevalence of infection in cattle, consumption of beef remains an important source of infection. Developing this QMRA model has helped identify important gaps of knowledge and resulted in the following recommendations for future research: collect processing-effect data in line with consumer style processing and acquire product specific heating temperatures, investigate the presence and concentration of viable bradyzoites in cattle, determine the effect of mincing meat on bradyzoite concentrations using actual batch sizes, and obtain an estimate of the fraction of meat that has been frozen prior to purchase. With more accurate data this QMRA model will aid science-based decision-making on intervention strategies to reduce the disease burden from meatborne T. gondii infections in The Netherlands.

Attributing the human disease burden of foodborne infections to specific sources.

Foodborne diseases are an important cause of human illness worldwide. Humans acquire these infections from a variety of sources and routes of transmission. Many efforts have been made in the last decades to prevent and control foodborne diseases, particularly foodborne zoonoses. However, information on the impact of these interventions is limited. To identify and prioritize successful food safety interventions, it is important to attribute the burden of human illness to the specific sources. Defining scientific concepts and harmonizing terminology for "source attribution" is essential for understanding and improving attribution methodologies and for sharing knowledge within the scientific community. We propose harmonized nomenclature, and describe the various approaches for human illness source attribution and their usefulness to address specific public health questions.

Effectiveness and efficiency of controlling Campylobacter on broiler chicken meat.

Campylobacter bacteria are an important cause of foodborne infections. We estimated the potential costs and benefits of a large number of possible interventions to decrease human exposure to Campylobacter by consumption of chicken meat, which accounts for 20-40% of all cases of human campylobacteriosis in the Netherlands. For this purpose, a farm-to-fork risk assessment model was combined with economic analysis and epidemiological data. Reduction of contamination at broiler farms could be efficient in theory. However, it is unclear which hygienic measures need to be taken and the costs can be very high. The experimental treatment of colonized broiler flocks with bacteriophages has proven to be effective and could also be cost efficient, if confirmed in practice. Since a major decrease of infections at the broiler farm is not expected in the short term, additional measures in the processing plant were also considered. At this moment, guaranteed Campylobacter-free chicken meat at the retail level is not realistic. The most promising interventions in the processing plant are limiting fecal leakage during processing and separation of contaminated and noncontaminated flocks (scheduling), followed by decontamination of the contaminated flock. New (faster and more sensitive) test methods to detect Campylobacter colonization in broilers flocks are a prerequisite for successful scheduling scenarios. Other methods to decrease the contamination of meat of colonized flocks such as freezing and heat treatment are more expensive and/or less effective than chemical decontamination.

Predicted quantitative effect of logistic slaughter on microbial prevalence.

Logistic slaughter is an intervention measure intended to reduce cross-contamination during slaughter by slaughtering contaminated units (=(groups of) animals) last. This paper describes a simple mathematical model which predicts the prevalences of contaminated units after logistic and random-order slaughter. The effect of logistic slaughter is the difference between these prevalences. The model assumes that uncontaminated units can become contaminated by contaminated units that were slaughtered before them; the contributions of contaminated units are independent. It also assumes that a slaughterhouse is uncontaminated at the start of the day and that a unit that is contaminated before slaughter also is contaminated after slaughter. The model was analysed using numerical simulations; for a selection of cases, analytical formulas can be derived and are presented. Contamination of broiler flocks with Salmonella was used as a case study. Even for this simple model, data availability is a problem leading to uncertain parameter estimates. An average cross-contamination scenario predicts that the beneficial effect of logistic slaughter is as low as 9.1%, which casts doubt on its usefulness as an intervention measure. The case study produced these general model results: the effect of logistic slaughter increases with the probability of cross-contamination between units; with the length of the slaughter queue; and with sensitivity (the probability of a positive test from a unit contaminated at the start of slaughter). However, the effect is small if the prevalence of contaminated units before slaughter is low or high.