Using Campylobacter spp. and Escherichia coli data and Bayesian microbial risk assessment to examine public health risks in agricultural watersheds under tile drainage management

2013 ◽  
Vol 47 (10) ◽  
pp. 3255-3272 ◽  
Author(s):  
P.J. Schmidt ◽  
K.D.M. Pintar ◽  
A.M. Fazil ◽  
C.A. Flemming ◽  
M. Lanthier ◽  
...  
Keyword(s):  
Public Health ◽  
Escherichia Coli ◽  
Risk Assessment ◽  
Health Risks ◽  
Tile Drainage ◽  
Agricultural Watersheds ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Public Health Risks ◽  
Campylobacter Spp

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

scholarly journals Molecular Analyses of Fecal Bacteria and Hydrodynamic Modeling for Microbial Risk Assessment of a Drinking Water Source

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 3
Author(s):  
Olga D. Chuquimia ◽  
Viktor Bergion ◽  
Jessica Guzman-Otazo ◽  
Kaisa Sörén ◽  
Lars Rosén ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Water Intake ◽  
Real Time Pcr ◽  
Hydrodynamic Modeling ◽  
Salmonella Spp ◽  
Molecular Analyses ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Campylobacter Spp

Safe water is a global concern, and methods to accurately monitor quality of water are vital. To assess the risks related to bacterial pathogen load in Lake Vomb that provides drinking water to the southern part of Sweden, this study combined molecular analyses of enterobacteria and bacterial pathogens in water using quantitiative real-time PCR with hydrodynamic modeling and quantitative microbial risk assessment (QMRA). A real-time PCR assay to detect enterobacteria was set up by primers targeting ssrA. Between February 2015 and May 2016, presence of ssrA gene copies as well as Campylobacter spp., Salmonella spp., and EHEC O157 DNA was analyzed by real-time PCR at several locations in the catchment of Lake Vomb and its tributaries Björkaån, Borstbäcken, and Torpsbäcken. Björkaån had the highest detected concentrations of the ssrA gene and, according to the results of hydrodynamic modeling, contributed most to the contamination of the water intake in the lake. None of the water samples were positive for genes encoding EHEC O157 and Campylobacter spp., while invA (Salmonella spp.) was present in 11 samples. The QMRA showed that the suggested acceptable risk level (daily probability of infection <2.7 × 10−7) is achieved with a 95% probability, if the Salmonella concentrations in the water intake are below 101 bacteria/100 mL. If a UV-disinfection step is installed, the Salmonella concentration at the water intake should not exceed 106 bacteria/100 mL.

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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