Quantitative Assessment of the Microbial Risk of Leafy Greens from Farm to Consumption: Preliminary Framework, Data, and Risk Estimates

2011 ◽  
Vol 74 (5) ◽  
pp. 700-708 ◽  
Author(s):  
MICHELLE D. DANYLUK ◽  
DONALD W. SCHAFFNER
Keyword(s):  
Risk Assessment ◽  
Risk Model ◽  
Assessment Model ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
E Coli ◽  
Leafy Greens ◽  
Risk Estimates ◽  
Washing Process

This project was undertaken to relate what is known about the behavior of Escherichia coli O157:H7 under laboratory conditions and integrate this information to what is known regarding the 2006 E. coli O157:H7 spinach outbreak in the context of a quantitative microbial risk assessment. The risk model explicitly assumes that all contamination arises from exposure in the field. Extracted data, models, and user inputs were entered into an Excel spreadsheet, and the modeling software @RISK was used to perform Monte Carlo simulations. The model predicts that cut leafy greens that are temperature abused will support the growth of E. coli O157:H7, and populations of the organism may increase by as much a 1 log CFU/day under optimal temperature conditions. When the risk model used a starting level of −1 log CFU/g, with 0.1% of incoming servings contaminated, the predicted numbers of cells per serving were within the range of best available estimates of pathogen levels during the outbreak. The model predicts that levels in the field of −1 log CFU/g and 0.1% prevalence could have resulted in an outbreak approximately the size of the 2006 E. coli O157:H7 outbreak. This quantitative microbial risk assessment model represents a preliminary framework that identifies available data and provides initial risk estimates for pathogenic E. coli in leafy greens. Data gaps include retail storage times, correlations between storage time and temperature, determining the importance of E. coli O157:H7 in leafy greens lag time models, and validation of the importance of cross-contamination during the washing process.

Quantitative microbial risk assessment applied to irrigation of salad crops with waste stabilization pond effluents

2013 ◽  
Vol 67 (6) ◽  
pp. 1208-1215 ◽  
Author(s):  
D. M. S. Pavione ◽  
R. K. X. Bastos ◽  
P. D. Bevilacqua
Keyword(s):  
Risk Assessment ◽  
Field Experiments ◽  
Daily Intake ◽  
Assessment Model ◽  
Sensitivity Analyses ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Risk Estimates ◽  
Log Normal

A quantitative microbial risk assessment model for estimating infection risks arising from consuming crops eaten raw that have been irrigated with effluents from stabilization ponds was constructed. A log-normal probability distribution function was fitted to a large database from a comprehensive monitoring of an experimental pond system to account for variability in Escherichia coli concentration in irrigation water. Crop contamination levels were estimated using predictive models derived from field experiments involving the irrigation of several crops with different effluent qualities. Data on daily intake of salad crops were obtained from a national survey in Brazil. Ten thousand-trial Monte Carlo simulations were used to estimate human health risks associated with the use of wastewater for irrigating low- and high-growing crops. The use of effluents containing 103–104E. coli per 100 ml resulted in median rotavirus infection risk of approximately 10−3 and 10−4 pppy when irrigating, respectively, low- and high-growing crops; the corresponding 95th percentile risk estimates were around 10−2 in both scenarios. Sensitivity analyses revealed that variations in effluent quality, in the assumed ratios of pathogens to E. coli, and in the reduction of pathogens between harvest and consumption had great impact upon risk estimates.

Comparing the Effect of Various Contamination Levels for Salmonella in Chicken Meat Preparations on the Probability of Illness in Belgium

2009 ◽  
Vol 72 (10) ◽  
pp. 2093-2105 ◽  
Author(s):  
MIEKE UYTTENDAELE ◽  
KATLEEN BAERT ◽  
KOEN GRIJSPEERDT ◽  
LIEVEN DE ZUTTER ◽  
BENOIT HORION ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Chicken Meat ◽  
Assessment Model ◽  
Contamination Level ◽  
Quantitative Microbial Risk Assessment ◽  
Risk Assessment Model ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Increased Risk ◽  
Fixed Input

At the urging of competent national authorities, a limited risk assessment on Salmonella in chicken meat preparations in Belgium was undertaken following a retail-to-table approach. The input distribution of Salmonella was based on surveillance data in Belgium. To analyze the relative impact of reducing the risk of salmonellosis associated with a decrease in the Salmonella contamination level, different distributions based on the actual situation but limiting the number of portions containing Salmonella at 1 CFU per 1, 10, and 25 g of meat were used in the quantitative microbial risk assessment model. The quantitative microbial risk assessment model also was run several times with a theoretical fixed input of Salmonella assuming all portions possessed the same fixed contamination level set at 1,000, 100, 10, and 1 CFU/g of meat and 1 CFU per 10, 25, 100, and 1,000 g of meat. With regard to the initial contamination level, the results indicate, both by the narrowing of the current distribution and by the fixed input, that especially the higher levels of contamination (>1 CFU/g) contribute to the increased risk for salmonellosis.

Quantitative Microbial Risk Assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes in Leafy Green Vegetables Consumed at Salad Bars

2010 ◽  
Vol 73 (2) ◽  
pp. 274-285 ◽  
Author(s):  
E. FRANZ ◽  
S. O. TROMP ◽  
H. RIJGERSBERG ◽  
H. J. van der FELS-KLERX
Keyword(s):  
Public Health ◽  
Escherichia Coli ◽  
Risk Assessment ◽  
Monte Carlo ◽  
Escherichia Coli O157 ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Public ◽  
E Coli

Fresh vegetables are increasingly recognized as a source of foodborne outbreaks in many parts of the world. The purpose of this study was to conduct a quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes infection from consumption of leafy green vegetables in salad from salad bars in The Netherlands. Pathogen growth was modeled in Aladin (Agro Logistics Analysis and Design Instrument) using time-temperature profiles in the chilled supply chain and one particular restaurant with a salad bar. A second-order Monte Carlo risk assessment model was constructed (using @Risk) to estimate the public health effects. The temperature in the studied cold chain was well controlled below 5°C. Growth of E. coli O157:H7 and Salmonella was minimal (17 and 15%, respectively). Growth of L. monocytogenes was considerably greater (194%). Based on first-order Monte Carlo simulations, the average number of cases per year in The Netherlands associated the consumption leafy greens in salads from salad bars was 166, 187, and 0.3 for E. coli O157:H7, Salmonella, and L. monocytogenes, respectively. The ranges of the average number of annual cases as estimated by second-order Monte Carlo simulation (with prevalence and number of visitors as uncertain variables) were 42 to 551 for E. coli O157:H7, 81 to 281 for Salmonella, and 0.1 to 0.9 for L. monocytogenes. This study included an integration of modeling pathogen growth in the supply chain of fresh leafy vegetables destined for restaurant salad bars using software designed to model and design logistics and modeling the public health effects using probabilistic risk assessment software.

scholarly journals Evaluating the Risk of Salmonellosis from Dry Roasted Sunflower Seeds

2019 ◽  
Vol 83 (1) ◽  
pp. 17-27 ◽  
Author(s):  
BALASUBRAHMANYAM KOTTAPALLI ◽  
STEPHANIE P. V. NGUYEN ◽  
KELLY DAWSON ◽  
KAITLYN CASULLI ◽  
CATE KNOCKENHAUER ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Water Activity ◽  
The United States ◽  
Arithmetic Mean ◽  
Assessment Model ◽  
Quantitative Microbial Risk Assessment ◽  
Sunflower Seeds ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Log Reduction

ABSTRACT Outbreaks and recalls related to nuts and seeds in the United States have increased recently, and 80% of these recalls are due to Salmonella. The U.S. Food and Drug Administration's Food Safety Modernization Act requires food manufacturers to implement risk-based preventive controls based on scientific and technical evidence. Data are limited on the inactivation of Salmonella during processing of saltwater brined in-shell sunflower seeds. The goal of this research was to validate the adequacy of roasting in controlling Salmonella during the production of sunflower seeds and to assess the resulting risk. Four Salmonella strains were inoculated onto sunflower seeds and processed to simulate commercial manufacturing. Seeds were tumbled and roasted at 225°F (107.2°C) and 275°F (135°C) for roasting times from 5 to 45 min. Regression models for Salmonella inactivation and water activity change were developed. The inactivation model predicted a 5-log reduction in Salmonella when sunflower seeds were roasted at 135°C for 19.2 min, with a corresponding water activity of ∼0.61. Roasted sunflower seeds are typically not saleable at water activities >0.6 due to quality issues. Saleable water activities (0.03 to 0.04) were only achieved when the sunflower seeds were roasted for 45 min at 135°C, which resulted in a >7-log reduction in Salmonella. A quantitative microbial risk assessment based on literature values, expert opinion, and the above-mentioned models was used to predict risk of salmonellosis from sunflower seeds. The quantitative microbial risk assessment model predicted an arithmetic mean probability of illness of 1.45E−07 per 28-g serving based on roasting at 135°C for 20 min and an arithmetic mean probability of illness of 5.46E−10 per serving based on roasting at 135°C for >45 min (i.e., saleable product process parameters). This study demonstrates that sunflower seeds roasted to saleable parameters should not represent a public health risk from potential presence of Salmonella.

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