A review of quantitative microbial risk assessment and consumer process models for Campylobacter in broiler chickens

Chapman, Brennan; Otten, Ainsley; Fazil, Aamir; Ernst, Natalie; Smith, Ben

doi:10.1016/j.mran.2016.07.001

Cited by 27 publications

(29 citation statements)

References 59 publications

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“…Most of the available cross-contamination models on the improper handling of raw chicken meat have been developed for Campylobacter spp. (Chapman, Otten, Fazil, Ernst, & Smith, 2016). However, in relation to resistant bacteria just one model describing the cross-contamination of ESBL/AmpC E. coli in meat can be found in the literature (Evers et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic model for the estimation of the consumer exposure to methicillin‐resistant Staphylococcus aureus due to cross‐contamination and recontamination

2019

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The presence of multidrug‐resistant bacteria like methicillin‐resistant Staphylococcus aureus (MRSA) in retail meat is one of the current concerns of the public health authorities. Bacterial cross‐contamination and recontamination during household food preparation could play an important role in the dissemination of such bacteria, and therefore could contribute to a serious health problem, more specifically for immunocompromised people. In order to evaluate the importance of such events, a probabilistic model was developed to estimate the likelihood and extent of cross‐contamination and recontamination and the burden of MRSA from contaminated raw chicken meat via hands and kitchen utensils in a serving (consisting on a slice of bread and a piece of grilled chicken meat) during a household barbecue in Germany. A modular design was used, taking into account the chronological order of the routines during the barbecue event, and Monte Carlo simulations were applied. Available data on the prevalence and burden of MRSA in chicken meat at retail in Germany were used as starting point and were incorporated in the model as probability distributions. The probabilities and extent of bacterial transfer between food items and kitchen utensils (referred to as “Objects”) and the routines performed during food preparation (referred to as “Actions”) specified by their probabilities of occurrence were incorporated as the main input parameters. The model was set up in R 3.5.0 and converted to a standardized format (FSKX file). Therefore, the code can be easily accessed, evaluated, modified, and reused for different purposes. The present study contributes to the quantification of consumer exposure to MRSA through food consumption once contaminated food has entered the household kitchen. Even when the MRSA prevalence and bacterial load in retail chicken meat in Germany are low, resistant bacteria can reach the consumer due to cross‐contamination and recontamination events. The results show that the probability of one CFU to be transferred from the contaminated raw chicken meat to the final serving and the number of MRSA bacteria transferred due to cross‐contamination and recontamination events are in general low, being the contamination of the final serving more likely to occur via bread, rather than via grilled chicken. The results show that the prevalence of MRSA at retail highly influences the probability of the final serving to be contaminated. However, this study also highlights the importance of keeping good hygiene practices during the household food manipulation for reducing the spread of MRSA. The provision of the model in a standardized data format will allow an easy incorporation of the developed model into a complete quantitative microbial risk assessment model that will greatly help to estimate the risk of consumer exposure to MRSA through the consumption of contaminated food.

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Section: Introductionmentioning

confidence: 99%

Probabilistic model for the estimation of the consumer exposure to methicillin‐resistant Staphylococcus aureus due to cross‐contamination and recontamination

2019

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“…It is not anticipated that transport or the stunning and killing process would result in increased growth or survivability of CSH in comparison with susceptible S . Heidelberg strains [124]. …”

Section: Results (Headings As Per the Codex Guidelines)mentioning

confidence: 99%

Ceftiofur-resistant Salmonella enterica serovar Heidelberg of poultry origin – a risk profile using the Codex framework

Carson

Agunos

et al. 2019

Epidemiol. Infect.

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Codex published the ‘Guidelines for Risk Analysis of Foodborne Antimicrobial Resistance’ to standardise the approach for evaluating risk posed by foodborne antimicrobial-resistant bacteria. One of the first steps in the guidelines is to compile a risk profile, which provides the current state of knowledge regarding a food safety issue, describes risk management options and recommends next steps. In Canada, ceftiofur/ceftriaxone-resistant Salmonella enterica subsp. enterica serovar Heidelberg from poultry was identified as an antimicrobial resistance (AMR) food safety issue. The first objective of this article was to contextualise this food safety issue, using the risk profile format of the Codex Guidelines. A second objective was to evaluate the applicability of the Codex Guidelines. This risk profile indicated that ceftiofur/ceftriaxone-resistant S. Heidelberg (CSH) was commonly isolated from poultry and was associated with severe disease in humans. Ceftiofur use in poultry hatcheries temporally mirrored the prevalence of CSH from poultry meat at retail and from people with salmonellosis. The evidence was sufficient to indicate the need for risk management options, such as restricting the use of ceftiofur in poultry. The Codex Guidelines provided a useful approach to summarise data for decision-makers to evaluate an AMR food safety issue.

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“…Given the increase in poultry consumption and the globalization of the food supply chain, food-borne pathogens in general and, Campylobacter spp. in particular, have become leading causes of human enteric infections worldwide [1,2]. In order to alleviate both the public health and socio-economic burden associated to such illnesses, re searchers have conducted numerous studies, attempting to enumerate pathogen prevalence and concentration at various processing stages (see for instance [3][4][5][6][7][8] and references therein).…”

Section: Introductionmentioning

confidence: 99%

“…In order to alleviate both the public health and socio-economic burden associated to such illnesses, re searchers have conducted numerous studies, attempting to enumerate pathogen prevalence and concentration at various processing stages (see for instance [3][4][5][6][7][8] and references therein). While the results from these studies are valuable in their own right, these findings have to be integrated to inform quantitative microbial risk assessment (QMRA) models as a management tool for food safety control [1,2]. Such "sto chastic risk models are robust tools that can be used for evidence-in formed decision-making, and are uniquely suited to manage a wide breadth of data and interpret the variability and uncertainty inherent of microbial populations" [1].…”

Section: Introductionmentioning

confidence: 99%

“…While the results from these studies are valuable in their own right, these findings have to be integrated to inform quantitative microbial risk assessment (QMRA) models as a management tool for food safety control [1,2]. Such "sto chastic risk models are robust tools that can be used for evidence-in formed decision-making, and are uniquely suited to manage a wide breadth of data and interpret the variability and uncertainty inherent of microbial populations" [1]. However, pathogen transfer probabilities at key steps during poultry processing may be unknown, difficult to ex tract from experimental studies, or loosely estimated, limiting the confidence in predictive results.…”

Section: Introductionmentioning

confidence: 99%

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Individual based modeling and analysis of pathogen levels in poultry chilling process

McCarthy

Smith

Fazil

et al. 2017

Mathematical Biosciences

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Pathogen control during poultry processing critically depends on more enhanced insight into contamination dynamics. In this study we build an individual based model (IBM) of the chilling process. Quantifying the relationships between typical Canadian processing specifications, water chemistry dynamics and pathogen levels both in the chiller water and on individual carcasses, the IBM is shown to provide a useful tool for risk management as it can inform risk assessment models. We apply the IBM to Campylobacter spp. contamination on broiler carcasses, illustrating how free chlorine (FC) sanitization, organic load in the water, and pre-chill carcass pathogen levels affect pathogen levels of post-chill broilers. In particular, given a uniform distribution of Campylobacter levels on incoming poultry we quantify the efficacy of FC control in not only reducing pathogen levels on average, but also the variation of pathogen levels on poultry exiting the chill tank. Furthermore, we demonstrate that the absence/presence of FC input dramatically influences when, during a continuous chilling operation, cross-contamination will be more likely.

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A review of quantitative microbial risk assessment and consumer process models for Campylobacter in broiler chickens

Cited by 27 publications

References 59 publications

Probabilistic model for the estimation of the consumer exposure to methicillin‐resistant Staphylococcus aureus due to cross‐contamination and recontamination

Probabilistic model for the estimation of the consumer exposure to methicillin‐resistant Staphylococcus aureus due to cross‐contamination and recontamination

Ceftiofur-resistant Salmonella enterica serovar Heidelberg of poultry origin – a risk profile using the Codex framework

Individual based modeling and analysis of pathogen levels in poultry chilling process

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