Quantifying the Risk of Human Toxoplasma gondii Infection Due to Consumption of Domestically Produced Lamb in the United States

2016 ◽  
Vol 79 (7) ◽  
pp. 1181-1187 ◽  
Author(s):  
MIAO GUO ◽  
ABHINAV MISHRA ◽  
ROBERT L. BUCHANAN ◽  
JITENDER P. DUBEY ◽  
DOLORES E. HILL ◽  
...  

ABSTRACT Toxoplasma gondii is a prevalent protozoan parasite worldwide. Human toxoplasmosis is responsible for considerable morbidity and mortality in the United States, and meat products have been identified as an important source of T. gondii infections in humans. The goal of this study was to develop a farm-to-table quantitative microbial risk assessment model to predict the public health burden in the United States associated with consumption of U.S. domestically produced lamb. T. gondii prevalence in market lambs was pooled from the 2011 National Animal Health Monitoring System survey, and the concentration of the infectious life stage (bradyzoites) was calculated in the developed model. A log-linear regression and an exponential dose-response model were used to model the reduction of T. gondii during home cooking and to predict the probability of infection, respectively. The mean probability of infection per serving of lamb was estimated to be 1.5 cases per 100,000 servings, corresponding to ~6,300 new infections per year in the U.S. population. Based on the sensitivity analysis, we identified cooking as the most effective method to influence human health risk. This study provided a quantitative microbial risk assessment framework for T. gondii infection through consumption of lamb and quantified the infection risk and public health burden associated with lamb consumption.

2019 ◽  
Vol 82 (4) ◽  
pp. 579-588 ◽  
Author(s):  
KAITLYN E. CASULLI ◽  
STEPHEN CALHOUN ◽  
DONALD W. SCHAFFNER

ABSTRACT Peanut products were the target of the largest food recall in United States history from 2008 to 2009, with more than 3,200 products implicated, economic losses estimated at $1 billion, and more than 700 reported illnesses and 9 deaths. Predictive modeling tools such as quantitative microbial risk assessment can be used to aid processors in making risk management decisions that may reduce the chances of foodborne illness, but published risk assessment for peanuts is not currently available. A quantitative microbial risk assessment was performed to quantify salmonellosis risk from consumption of peanuts in the United States. Prevalence and concentration data for Salmonella on raw, shelled peanuts were used in combination with probability distributions of simulated log reductions achieved during production steps before consumption. Data for time-temperature combinations used in each step were obtained from published literature, industry surveys, or expert opinion, and survival data were obtained from the literature. A beta-Poisson dose-response model was used to predict probability of illness from ingestion of Salmonella cells. The model predicted 14.2 (arithmetic mean) or 0.0123 (geometric mean) illnesses per year. Sensitivity analysis showed that thermal inactivation log reductions applied had the biggest impact on predicted salmonellosis risk, followed by consumer storage time, Salmonella starting concentration, Salmonella starting prevalence, and number of originally contaminated 25-g servings per originally positive 375-g sample. Scenario analysis showed that increasing log reduction variability increased mean salmonellosis risk. Removing the effect of storage on Salmonella survival increased the arithmetic and geometric means to 153 and 0.598 illnesses per year, respectively. This study indicated that the risk of salmonellosis from consumption of peanuts can be lowered by reducing field contamination, control of storage steps, and monitoring of appropriate critical limits in peanut roasting.


2014 ◽  
Vol 7 (2) ◽  
pp. 212-217 ◽  
Author(s):  
Eric C. Stecker ◽  
Kyndaron Reinier ◽  
Eloi Marijon ◽  
Kumar Narayanan ◽  
Carmen Teodorescu ◽  
...  

2016 ◽  
Vol 2 (4) ◽  
pp. 599-613 ◽  
Author(s):  
K. A. Hamilton ◽  
C. N. Haas

Legionellahas been identified as the responsible agent for two-thirds of waterborne disease outbreaks in the United States from 2011–2012.


2010 ◽  
Vol 73 (2) ◽  
pp. 274-285 ◽  
Author(s):  
E. FRANZ ◽  
S. O. TROMP ◽  
H. RIJGERSBERG ◽  
H. J. van der FELS-KLERX

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.


2019 ◽  
Vol 83 (1) ◽  
pp. 17-27 ◽  
Author(s):  
BALASUBRAHMANYAM KOTTAPALLI ◽  
STEPHANIE P. V. NGUYEN ◽  
KELLY DAWSON ◽  
KAITLYN CASULLI ◽  
CATE KNOCKENHAUER ◽  
...  

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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