Developing a risk management framework to improve public health outcomes by enumerating and serotyping Salmonella in ground turkey.

Salmonella enterica continues to be a leading cause of foodborne morbidity worldwide. A quantitative risk assessment model was developed to evaluate the impact of pathogen enumeration and serotyping strategies on public health after consumption of undercooked contaminated ground turkey in the USA. The risk assessment model predicted more than 20,000 human illnesses annually that would result in ~700 annual reported cases. Removing ground turkey lots contaminated with Salmonella exceeding 10 MPN/g, 1 MPN/g, and 1 MPN/25 g would decrease the mean number of illnesses by 38.2, 73.1, and 95.0%, respectively. A three-class mixed sampling plan was tested to allow the detection of positive lots above threshold levels with 2-6 (c = 1) and 3-8 samples per lot (c = 2) using 25-g and 325-g sample sizes for a 95% probability of rejecting a contaminated lot. Removal of positive lots with the presence of highly virulent serotypes would decrease the number of illnesses by 44.2-87.0%. Based on these model prediction results, risk management strategies should incorporate pathogen enumeration and/or serotyping. This would have a direct impact on illness incidence linking public health outcomes with measurable food safety objectives, at the cost of diverting production lots.

Risk ranking of food categories associated with Salmonella enterica contamination in the central region of Mexico.

To prevent and control foodborne diseases, there is a fundamental need to identify the foods that are most likely to cause illness. The goal of this study was to rank 25 commonly consumed food products associated with Salmonella enterica contamination in the Central Region of Mexico. A multicriteria decision analysis (MCDA) framework was developed to obtain an S. enterica risk score for each food product based on four criteria: probability of exposure to S. enterica through domestic food consumption (Se); S. enterica growth potential during home storage (Sg); per capita consumption (Pcc); and food attribution of S. enterica outbreak (So). Risk scores were calculated by the equation Se*W1 +Sg*W2 +Pcc*W3 +So*W4 , where each criterion was assigned a normalized value (1-5) and the relative weights (W) were defined by 22 experts' opinion. Se had the largest effect on the risk score being the criterion with the highest weight (35%; IC95% 20%-60%), followed by So (24%; 5%-50%), Sg (23%; 10%-40%), and Pcc (18%; 10%-35%). The results identified chicken (4.4 ± 0.6), pork (4.2 ± 0.6), and beef (4.2 ± 0.5) as the highest risk foods, followed by seed fruits (3.6 ± 0.5), tropical fruits (3.4 ± 0.4), and dried fruits and nuts (3.4 ± 0.5), while the food products with the lowest risk were yogurt (2.1 ± 0.3), chorizo (2.1 ± 0.4), and cream (2.0 ± 0.3). Approaches with expert-based weighting and equal weighting showed good correlation (R2  = 0.96) and did not show significant differences among the ranking order in the top 20 tier. This study can help risk managers select interventions and develop targeted surveillance programs against S. enterica in high-risk food products.

Genotypic and phenotypic quantitative microbial risk assessment model of human salmonellosis related to the consumption of chicken meat in the central region of Mexico.

Chicken meat is often associated withSalmonella entericacontamination worldwide. This study proposes a risk assessment model for human salmonellosis linked to the domestic consumption of chicken meat in the central region of Mexico, incorporating genotypic and phenotypic data. SixS. entericagroups were used, considering the presence of specific virulence genes and multidrug resistance (MDR). Sixteen exposure scenarios were established considering retail point (RP1 = fresh market/butcher shop; RP2 = mini-super/supermarket), transportation, home storage, cooking, and cross-contamination. The model predicted a mean annual salmonellosis cases of 66,754 due to chicken consumption (CI95% 10775-231606). The mean probability of illness (Pill) among the exposure scenarios ranged from 2.5 × 10-9 to 3.7 × 10-6, 7.7 × 10-8 to 1.1 × 10-4, and 6.7 × 10-4 to 7.8 × 10-2 for low, moderate, and high virulence groups. Exposure scenarios with the highest Pill were not responsible for most cases due to their low frequency of occurrence. The high virulence/ MDR group was responsible for most cases (66.5 %), despite the low S. enterica prevalence (RP1 0.5 % and RP2 5.0 %). The years lost due to disability (YLD) value for MDR was 2.6 × higher than for non-MDR. Spearman rank showed that the inputs with higher influence on the variability of salmonellosis depended on the type of exposure scenario. For example, the cooking temperature and time had the most significant influence in the scenarios where S. enterica can survive after cooking. Including the microbial genotypic and phenotypic characteristics in risk assessment modeling highlights the importance of focusing on high-virulent and MDR strains, which are not the most frequent but represent the highest public health risk.

Guidance on validation of lethal control measures for foodborne pathogens in foods.

Food manufacturers are required to obtain scientific and technical evidence that a control measure or combination of control measures is capable of reducing a significant hazard to an acceptable level that does not pose a public health risk under normal conditions of distribution and storage. A validation study provides evidence that a control measure is capable of controlling the identified hazard under a worst-case scenario for process and product parameters tested. It also defines the critical parameters that must be controlled, monitored, and verified during processing. This review document is intended as guidance for the food industry to support appropriate validation studies, and aims to limit methodological discrepancies in validation studies that can occur among food safety professionals, consultants, and third-party laboratories. The document describes product and process factors that are essential when designing a validation study, and gives selection criteria for identifying an appropriate target pathogen or surrogate organism for a food product and process validation. Guidance is provided for approaches to evaluate available microbiological data for the target pathogen or surrogate organism in the product type of interest that can serve as part of the weight of evidence to support a validation study. The document intends to help food manufacturers, processors, and food safety professionals to better understand, plan, and perform validation studies by offering an overview of the choices and key technical elements of a validation plan, the necessary preparations including assembling the validation team and establishing prerequisite programs, and the elements of a validation report.

Relationships of Water Activity and Moisture Content to the Thermal Inactivation Kinetics of Salmonella in Low-Moisture Foods.

HIGHLIGHTS: Water affects thermal inactivation kinetics of Salmonella in low-moisture foods. Water activity and moisture content are both feasible predictors of heat resistance. Sorption state of food materials may affect Salmonella heat resistance.

Impact of Process Temperature, Humidity, and Initial Product Moisture on Thermal Inactivation of Salmonella Enteritidis PT 30 on Pistachios during Hot-Air Heating.

Some thermal processes, such as pistachio roasting, are not yet well characterized with respect to the impact of product and process variables on Salmonella lethality. This study aimed to quantify the effects of process temperature, humidity, and initial product water activity (aw), on Salmonella lethality for in-shell pistachios. In-shell pistachios were inoculated with Salmonella Enteritidis PT 30 (∼8.5 log CFU/g), equilibrated (0.45 or 0.65 aw), and heated without soaking ("dry") or after a pure-water or 27% NaCl brining pretreatment ("presoaked"). Inoculated pistachio samples (15 g) were heated in a laboratory-scale, moist-air convection oven at 104.4 or 118.3°C, humidities of ∼3, 15, or 30%, v/v (∼24.4, 54.4, or 69.4°C dew point), and air speed of 1.3 m/s. Salmonella survivors were quantified at six times during each treatment, targeting total reductions of ∼3 to 5 log. Survivor data were analyzed using analysis of variance to identify main effects (time, temperature, humidity, and initial aw) and two-term interactions with time. As expected, lethality increased ( P < 0.05) with temperature and humidity. For example, the time to achieve a 4-log reduction decreased 50 to 80% when humidity increased from ∼3 to 30%. When the dry and presoaked treatments were analyzed separately, initial product aw (0.45 versus 0.65 aw or 0.75 versus 0.95 aw) did not affect lethality ( P > 0.05). However, when comparing dry against presoaked treatments, the time to achieve a 4-log reduction decreased 55 to 85% ( P < 0.05) for presoaked pistachios subjected to the same temperature-humidity treatment. Salt had no effect ( P > 0.05) on lethality outcomes. These results, relative to initial aw, process humidity, brining, and salt effects on process lethality, are critically important and must be considered in the design and validation of thermal processes for Salmonella reduction in pistachio processing.

Effects of Inoculation Procedures on Variability and Repeatability of Salmonella Thermal Resistance in Wheat Flour.

Limited prior research has shown that inoculation methods affect thermal resistance of Salmonella in low-moisture foods; however, these effects and their repeatability have not been systematically quantified. Consequently, method variability across studies limits utility of individual data sets and cross-study comparisons. Therefore, the objective was to evaluate the effects of inoculation methodologies on stability and thermal resistance of Salmonella in a low-moisture food (wheat flour), and the repeatability of those results, based on data generated by two independent laboratories. The experimental design consisted of a cross-laboratory comparison, both conducting isothermal Salmonella inactivation studies in wheat flour (~0.45 water activity, 80°C), utilizing five different inoculation methods: (i) broth-based liquid inoculum, (ii) lawn-based liquid inoculum, (iii) lawn-based pelletized inoculum, (iv) direct harvest of lawn culture with wheat flour, and (v) fomite transfer of a lawn culture. Inoculated wheat flour was equilibrated ~5 days to ~0.45 water activity and then was subjected to isothermal treatment (80°C) in aluminum test cells. Results indicated that inoculation method impacted repeatability, population stability, and inactivation kinetics (α = 0.05), regardless of laboratory. Salmonella inoculated with the broth-based liquid inoculum method and the fomite transfer of a lawn culture method exhibited instability during equilibration. Lawn-based cultures resulted in stable populations prior to thermal treatment; however, the method using direct harvest of lawn culture with wheat flour yielded different D-values across the laboratories (α = 0.05), which was attributed to larger potential impact of operator variability. The lawn-based liquid inoculum and the lawn-based pelletized inoculum methods yielded stable inoculation levels and repeatable D-values (~250 and ~285 s, respectively). Also, inoculation level (3 to 8 log CFU/g) did not affect D-values (using the lawn-based liquid inoculum method). Overall, the results demonstrate that inoculation methods significantly affect Salmonella population kinetics and subsequent interpretation of thermal inactivation data for low-moisture foods.

Use of simulation tools to illustrate the effect of data management practices for low and negative plate counts on the estimated parameters of microbial reduction models.

In the last 20 years, the use of microbial reduction models has expanded significantly, including inactivation (linear and nonlinear), survival, and transfer models. However, a major constraint for model development is the impossibility to directly quantify the number of viable microorganisms below the limit of detection (LOD) for a given study. Different approaches have been used to manage this challenge, including ignoring negative plate counts, using statistical estimations, or applying data transformations. Our objective was to illustrate and quantify the effect of negative plate count data management approaches on parameter estimation for microbial reduction models. Because it is impossible to obtain accurate plate counts below the LOD, we performed simulated experiments to generate synthetic data for both log-linear and Weibull-type microbial reductions. We then applied five different, previously reported data management practices and fit log-linear and Weibull models to the resulting data. The results indicated a significant effect (α = 0.05) of the data management practices on the estimated model parameters and performance indicators. For example, when the negative plate counts were replaced by the LOD for log-linear data sets, the slope of the subsequent log-linear model was, on average, 22% smaller than for the original data, the resulting model underpredicted lethality by up to 2.0 log, and the Weibull model was erroneously selected as the most likely correct model for those data. The results demonstrate that it is important to explicitly report LODs and related data management protocols, which can significantly affect model results, interpretation, and utility. Ultimately, we recommend using only the positive plate counts to estimate model parameters for microbial reduction curves and avoiding any data value substitutions or transformations when managing negative plate counts to yield the most accurate model parameters.