<i>Salmonella</i> Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Oscar, Thomas P.

doi:10.1111/risa.13563

Cited by 24 publications

(17 citation statements)

References 71 publications

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“…Pathogen prevalence is part of the equation, and several other variables, such as quantification, are necessary to make decisions that will improve the food-safety system's performance. There have been models published identifying risk factors for Salmonella control in poultry-processing operations [29], which support the conclusions of the current study. Published risk assessments support this approach, and the results of the current study can be used to conduct probabilistic quantitative microbial risk assessments similar to those conducted in prior publications (QMRA) [30].…”

Section: Discussionsupporting

confidence: 88%

“…Even though the prevalence reduction is close to 50%, in quantification, the average reduction from live receiving to rehanger locations (2.27 log CFU/Sample for CX and 1.94 log CFU/Sample for RC) was higher than 90% with the CX treatment and 75% with the RC treatment, and it can only be seen with quantification data. These discrepancies are a confirmation than prevalence alone is not a good indicator of food safety [29].…”

Section: Salmonella Sppmentioning

confidence: 94%

“…Similarly, under the RC treatment, the prevalence of Campylobacter spp. remains between 85% and 100% through the post-IOBW #1 location, disregarding the reduction in counts from live receiving to rehanger of 3.23 log CFU/mL, which is a strong evidence that prevalence alone cannot be used as a sole representation of the microbial loads within a poultry-processing facility [29].…”

Section: Campylobacter Sppmentioning

confidence: 97%

See 2 more Smart Citations

Bio-Mapping Indicators and Pathogen Loads in a Commercial Broiler Processing Facility Operating with High and Low Antimicrobial Intervention Levels

Villena

Vargas

López

et al. 2022

Foods

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The poultry industry in the United States has traditionally implemented non-chemical and chemical interventions against Salmonella spp. and Campylobacter spp. on the basis of experience and word-of-mouth information shared among poultry processors. The effects of individual interventions have been assessed with microbiological testing methods for Salmonella spp. and Campylobacter spp. prevalence as well as quantification of indicator organisms, such as aerobic plate counts (APC), to demonstrate efficacy. The current study evaluated the loads of both indicators and pathogens in a commercial chicken processing facility, comparing the “normal chemical”, with all chemical interventions turned-on, at typical chemical concentrations set by the processing plant versus low-chemical process (“reduced chemical”), where all interventions were turned off or reduced to the minimum concentrations considered in the facility’s HACCP system. Enumeration and prevalence of Salmonella spp. and Campylobacter spp. as well as indicator organisms (APC and Enterobacteriaceae—EB) enumeration were evaluated to compare both treatments throughout a 25-month sampling period. Ten locations were selected in the current bio-mapping study, including live receiving, rehanger, post eviscerator, post cropper, post neck breaker, post IOBW #1, post IOBW #2, prechilling, post chilling, and parts (wings). Statistical process control parameters for each location and processing schemes were developed for each pathogen and indicator evaluated. Despite demonstrating significant statistical differences between the normal and naked processes in Salmonella spp. counts (“normal” significantly lower counts than the “reduced” at each location except for post-eviscerator and post-cropper locations), the prevalence of Salmonella spp. after chilling is comparable on both treatments (~10%), whereas for Campylobacter spp. counts, only at the parts’ location was there significant statistical difference between the “normal chemical” and the “reduced chemical”. Therefore, not all chemical intervention locations show an overall impact on Salmonella spp. or Campylobacter spp., and certain interventions can be turned off to achieve the same or better microbial performance if strategic intervention locations are enhanced.

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Section: Discussionsupporting

confidence: 88%

Section: Salmonella Sppmentioning

confidence: 94%

Section: Campylobacter Sppmentioning

confidence: 97%

See 1 more Smart Citation

Bio-Mapping Indicators and Pathogen Loads in a Commercial Broiler Processing Facility Operating with High and Low Antimicrobial Intervention Levels

Villena

Vargas

López

et al. 2022

Foods

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“…While traditionally MC have focused on the proportion of samples positive for the pathogen of interest (prevalence‐based MC), recent studies have highlighted the potential effectiveness of MC based on pathogen concentration in samples (concentration‐based MC) (Lambertini, Ruzante, Chew, Apodaca, & Kowalcyk, 2019 ; Oscar, 2020 ; Sampedro, Wells, Bender, & Hedberg, 2018 ). One study focused on chicken parts (Lambertini et al., 2019 ) while the second, conducted by another research group in parallel with the assessment presented here, examined the public health impact of implementing pathogen enumeration strategies to determine product acceptance in ground turkey (Sampedro et al., 2018 ).…”

Section: Introductionmentioning

confidence: 99%

The Public Health Impact of Implementing a Concentration‐Based Microbiological Criterion for Controlling Salmonella in Ground Turkey

2020

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Despite initiatives to improve the safety of poultry products in the United States, progress has stalled, and salmonellosis incidence is still above Healthy People 2020's goal. One strategy to manage Salmonella and verify process control in poultry establishments is to implement microbiological criteria (MC) linked to public health outcomes. Concentration‐based MC have been used by the food industry; however, the public health impact of such approaches is only starting to be assessed. This study evaluated the public health impact of a concentration‐based MC for Salmonella in raw ground turkey consumed in the United States using a quantitative risk assessment modeling approach. The distribution of Salmonella concentration in ground turkey was derived from USDA‐FSIS monitoring surveys. Other variables and parameters were derived from public databases, literature, and expert opinion. Based on considered concentrations, implementing a MC of 1 cell/g led to an estimated 46.1% reduction (preventable fraction, PF) in the mean probability of illness when consumer cooking and cross‐contamination were included. The PF was consistent across scenarios including or excluding cross‐contamination and cooking, with slightly lower mean PF when cross‐contamination was included. The proportion of lots not compliant with the 1 cell/g MC was 1.05% in the main scenarios and increased nonlinearly when higher Salmonella concentrations were assumed. Assumptions on concentration variability across lots and within lots had a large impact, highlighting the benefit of reducing this uncertainty. These approach and results can help inform the development of MC to monitor and control Salmonella in ground turkey products.

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“…Studies such as those assessing the "presence/absence" of the organism on-farm can associate common characteristics (e.g., the presence of dusty and dry conditions in houses) and their potential link to increased Salmonella prevalence on-farm (Berghaus et al, 2012). However, Salmonella prevalence in one of several risk factors for addressing salmonellosis (Oscar, 2020). Thus, merely assessing prevalence does not reveal the impact of the various management practices adopted, housing options, or the environmental fate of Salmonella on-farm (Payne et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Re-used or New Bedding Are Not Drivers of Salmonella Levels and Serovar Emergence in Commercially Farmed Broilers in Australia

Chinivasagam

Estella

Rodrigues

et al. 2022

Front. Sustain. Food Syst.

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To inform Salmonella on-farm management during broiler rearing, a 2-year study on two farms compared the Australian practices of new bedding use, partial litter re-use and an alternative, full litter re-use. Six sequential commercial cycles of ~50 days each were tested on each farm, on ~day 7 from placement (litter only), prior to first thin-out, and prior to final removal (litter and ceca). A random number sample collection occurred, defined by shed supports (33, 39), different drinkers, feeders, and shed center. Across the six cycles on both farms, Salmonella levels in ceca just prior to thin-out on full re-use litter were higher (log 3.11 MPN/g, P = 0.008) than for new bedding (log 2.04 MPN/g) and partial re-use (log 2.43 MPN/g) litter (the latter two were not significantly different). Prior to final removal across all practices the Salmonella levels in ceca from new bedding (log 1.72 MPN/g), partial re-use litter (log 1.77 MPN/g), and full re-use litter (log 2.33 MPN/g) were not statistically different, suggesting no effect of litter practice. The Salmonella levels in litter prior to the first (log 1.96–2.31 MPN/g) and second (log 2.24–2.48 MPN/g) removals were also not statistically different. The emergence of Salmonella serovars in the partitioned chicken-free grow-out end (back) of all sheds at ~day 7 did not suggest carry-over. Both the pattern of emergence of Salmonella serovars and Salmonella levels in litter ~day 7 in the brooder-end with chickens (front), suggested the Salmonella present were due to flock contribution and not practice driven. The dominant Salmonella serovar across cycles on both farms was S. Sofia (75 and 77% isolates) followed by S. Typhimurium (11 and 17%). Irrespective of initial serovars, Salmonella Sofia rapidly gained dominance and displaced 14 other serovars including S. Typhimurium on both farms. This study demonstrates that the litter practices are not the major driver of Salmonella prevalence in broiler farming, supporting the commercial re-use of bedding as a sustainable farming practice in Australia. The major contributor of Salmonella load in production is the Salmonella status of the incoming flock, indicating this is the key area to focus future control measures.

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

Cited by 24 publications

References 71 publications

Bio-Mapping Indicators and Pathogen Loads in a Commercial Broiler Processing Facility Operating with High and Low Antimicrobial Intervention Levels

Bio-Mapping Indicators and Pathogen Loads in a Commercial Broiler Processing Facility Operating with High and Low Antimicrobial Intervention Levels

The Public Health Impact of Implementing a Concentration‐Based Microbiological Criterion for Controlling Salmonella in Ground Turkey

Re-used or New Bedding Are Not Drivers of Salmonella Levels and Serovar Emergence in Commercially Farmed Broilers in Australia

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