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.

A review of quantitative microbial risk assessment in the management of Escherichia coli O157:H7 on beef

Meat Science ◽  
2006 ◽  
Vol 74 (1) ◽  
pp. 76-88 ◽  
Author(s):  
Geraldine Duffy ◽  
Enda Cummins ◽  
Pádraig Nally ◽  
Stephen O’ Brien ◽  
Francis Butler
Keyword(s):  
Escherichia Coli ◽  
Risk Assessment ◽  
Escherichia Coli O157 ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk

Quantitative Microbial Risk Assessment for Escherichia coli O157 on Lettuce, Based on Survival Data from Controlled Studies in a Climate Chamber

2011 ◽  
Vol 74 (12) ◽  
pp. 2000-2007 ◽  
Author(s):  
JAKOB R. OTTOSON ◽  
KARIN NYBERG ◽  
ROLAND LINDQVIST ◽  
ANN ALBIHN
Keyword(s):  
Escherichia Coli ◽  
Water Quality ◽  
Risk Assessment ◽  
Light Intensity ◽  
Risk Reduction ◽  
Escherichia Coli O157 ◽  
Quantitative Microbial Risk Assessment ◽  
Climate Chamber ◽  
Microbial Risk Assessment ◽  
Microbial Risk

The aims of the study were to determine the survival of Escherichia coli O157 on lettuce as a function of temperature and light intensity, and to use that information in a screening-level quantitative microbial risk assessment (QMRA) in order to evaluate risk-reducing strategies including irrigation water quality guidelines, rinsing, and holding time between last irrigation and harvest. Iceberg lettuce was grown in a climate chamber and inoculated with E. coli O157. Bacterial numbers were determined with the standard plate count method after inoculation and 1, 2, 4, and 7 day(s) postinoculation. The experiments were carried out at 11, 18, and 25°C in light intensities of 0, 400, and 600 mmol (m2)−1 s−1. There was a significant effect of temperature and light intensity on survival, with less bacteria isolated from lettuce incubated at 25 and 18°C compared with 11°C (P < 0.0001), and in light intensities of 400 and 600 mmol (m2)−1 s−1 compared with 0 mmol (m2)−1 s−1 (P < 0.001). The average log reductions after 1, 2, 4, and 7 day(s) were 1.14, 1.71, 2.04, and 3.0, respectively. The QMRA compared the relative risk with lettuce consumption from 20 scenarios. A stricter water quality guideline gave a mean fivefold risk reduction. Holding times of 1, 2, 4, and 7 day(s) reduced the risk 3, 8, 8, and 18 times, respectively, compared with harvest the same day as the last irrigation. Finally, rinsing lettuce for 15 s in cold tap water prior to consumption gave a sixfold risk reduction compared with eating unrinsed lettuce. Sensitivity analyses indicated that variation in bacterial inactivation had the most significant effect on the risk outcome. A QMRA determining the relative risks between scenarios reduces uncertainty and can provide risk managers with decision support.

scholarly journals Quantifying public health risks from exposure to waterborne pathogens during river bathing as a basis for reduction of disease burden

2020 ◽  
Vol 18 (3) ◽  
pp. 292-305
Author(s):  
M. M. Majedul Islam ◽  
Md. Atikul Islam
Keyword(s):  
Public Health ◽  
Health Risk ◽  
Quantitative Microbial Risk Assessment ◽  
Public Health Risk ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Public ◽  
E Coli ◽  
Untreated Sewage ◽  
Three Rivers

Abstract A Quantitative Microbial Risk Assessment (QMRA) technique was applied to assess the public health risk from exposure to infectious microorganisms at bathing areas of three rivers in Bangladesh. The QMRA assessed the probability of illness due to the accidental ingestion of river water impacted by untreated sewage. The simplified QMRA was based on average concentrations of four reference pathogens Escherichia coli (E. coli) O157:H7, Cryptosporidium spp, norovirus and rotavirus relative to indicator bacterium E. coli. Public health risk was estimated as the probability of infection and illness from a single exposure of bathers. The risks of illness were ranged from 7 to 10% for E. coli O157:H7, 13 to 19% for Cryptosporidium, 7 to 10% for norovirus and 12 to 17% for rotavirus. The overall risk of illness at the rivers was slightly higher in children (9–19%) compared to adults (7–16%). The risks of illness in individuals exposed to the river bathing were unacceptably high, exceeding the USEPA acceptable risk of 3–6 illnesses per hundred bathing events. This study gives a basis for reducing the burden of disease in the population by applying appropriate risk management. Findings and methods of this study will be helpful for other countries with similar socio-economic and geographic settings.

Monte Carlo Simulation Model for Predicting Salmonella Contamination of Chicken Liver as a Function of Serving Size for Use in Quantitative Microbial Risk Assessment

2021 ◽  
Author(s):  
Thomas Oscar
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Chicken Liver ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Serving Size ◽  
Monte Carlo Simulation Model

The first step in quantitative microbial risk assessment (QMRA) is to determine distribution of pathogen contamination among servings of the food at some point in the farm-to-table chain. In the present study, distribution of Salmonella contamination among servings of chicken liver for use in QMRA was determined at meal preparation. A combination of five methods: 1) whole sample enrichment; 2) quantitative polymerase chain reaction; 3) cultural isolation; 4) serotyping; and 5) Monte Carlo simulation were used to determine Salmonella prevalence (P), number (N), and serotype for different serving sizes. In addition, epidemiological data were used to convert serotype data to virulence (V) values for use in QMRA. A Monte Carlo simulation model based in Excel and simulated with @Risk predicted Salmonella P, N, serotype, and V as a function of serving size from one (58 g) to eight (464 g) chicken livers. Salmonella P of chicken livers was 72.5% (58/80) per 58 g. Four serotypes were isolated from chicken livers: 1) Infantis (P = 28%, V = 4.5); 2) Enteritidis (P = 15%, V = 5); 3) Typhimirium (P = 15%, V = 4.8); and 4) Kentucky (P = 15%, V = 0.8). Median Salmonella N was 1.76 log per 58 g (range: 0 to 4.67 log/58 g) and was not affected ( P > 0.05) by serotype. The model predicted a non-linear increase ( P ≤ 0.05) of Salmonella P from 72.5% per 58 g to 100% per 464 g, minimum N from 0 log per 58 g to 1.28 log per 464 g, and median N from 1.76 log per 58 g to 3.22 log per 464 g. Regardless of serving size, predicted maximum N was 4.74 log, mean V was 3.9, and total N was 6.65 log per lot (10,000 chicken livers). The data acquired and model developed in this study fill an important data and modeling gap in QMRA for Salmonella and chicken liver.

Modeling Food Spoilage in Microbial Risk Assessment

2009 ◽  
Vol 72 (2) ◽  
pp. 425-427 ◽  
Author(s):  
KONSTANTINOS KOUTSOUMANIS
Keyword(s):  
Escherichia Coli ◽  
Risk Assessment ◽  
Exposure Assessment ◽  
Systematic Approach ◽  
Ground Beef ◽  
Escherichia Coli O157 ◽  
Food Spoilage ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Combining Data

In this study, I describe a systematic approach for modeling food spoilage in microbial risk assessment that is based on the incorporation of kinetic spoilage modeling in exposure assessment by combining data and models for the specific spoilage organisms (SSO: fraction of the total microflora responsible for spoilage) with those for pathogens. The structure of the approach is presented through an exposure assessment application for Escherichia coli O157:H7 in ground beef. The proposed approach allows for identifying spoiled products at the time of consumption by comparing the estimated level of SSO (pseudomonads) with the spoilage level (level of SSO at which spoilage is observed). The results of the application indicate that ignoring spoilage in risk assessment could lead to significant overestimations of risk.

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