Food Risk Analysis

Oscar, Thomas P.

doi:10.1007/978-1-4614-1177-2_12

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Thus, Salmonella prevalence alone was not a good indicator of poultry food safety when multiple risk factors were considered. This conclusion is in agreement with other studies (Oscar, 1998, 2004b, 2011b, 2012a, 2012b, 2016, 2017b, 2018b, 2019; Sampedro et al., 2018).…”

Section: Discussionsupporting

confidence: 94%

Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Oscar

2020

Risk Analysis

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Salmonella is a leading cause of foodborne illness (i.e., salmonellosis) outbreaks, which on occasion are attributed to ground turkey. The poultry industry uses Salmonella prevalence as an indicator of food safety. However, Salmonella prevalence is only one of several factors that determine risk of salmonellosis. Consequently, a model for predicting risk of salmonellosis from individual lots of ground turkey as a function of Salmonella prevalence and other risk factors was developed. Data for Salmonella contamination (prevalence, number, and serotype) of ground turkey were collected at meal preparation. Scenario analysis was used to evaluate effects of model variables on risk of salmonellosis. Epidemiological data were used to simulate Salmonella serotype virulence in a dose‐response model that was based on human outbreak and feeding trial data. Salmonella prevalence was 26% (n = 100) per 25 g of ground turkey, whereas Salmonella number ranged from 0 to 1.603 with a median of 0.185 log per 25 g. Risk of salmonellosis (total arbitrary units (AU) per lot) was affected (p ≤ 0.05) by Salmonella prevalence, number, and virulence, by incidence and extent of undercooking, and by food consumption behavior and host resistance but was not (p > 0.05) affected by serving size, serving size distribution, or total bacterial load of ground turkey when all other risk factors were held constant. When other risk factors were not held constant, Salmonella prevalence was not correlated (r = −0.39; p = 0.21) with risk of salmonellosis. Thus, Salmonella prevalence alone was not a good indicator of poultry food safety because other factors were found to alter risk of salmonellosis. In conclusion, a more holistic approach to poultry food safety, such as the process risk model developed in the present study, is needed to better protect public health from foodborne pathogens like Salmonella.

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Section: Discussionsupporting

confidence: 94%

Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Oscar

2020

Risk Analysis

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“…A previously published disease triangle modeling method (12)(13)(14) was modified and used to simulate doseresponse in the current study. Two modifications made in the present study were that instead of two categories of risk per disease triangle factor and eight pert distributions for illness dose, five categories of risk per disease triangle factor, and 21 pert distributions for illness dose were used ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…These examples are provided to illustrate the thought process behind the modified disease triangle modeling method used in the current study. For a further description and discussion of this dose-response modeling method, please see previous studies (12)(13)(14).…”

Section: Resultsmentioning

confidence: 99%

Risk of Salmonellosis from Chicken Parts Prepared from Whole Chickens Sold in Flow Pack Wrappers and Subjected to Temperature Abuse

Oscar

2017

Journal of Food Protection

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The flow pack wrapper is a popular packaging choice for retail sale of whole chickens. However, it may provide a favorable environment for growth and spread of Salmonella within the package, leading to an outbreak of salmonellosis. To investigate this possibility, a process risk model was developed that predicted the risk of salmonellosis from chicken parts prepared from whole chickens sold in flow pack wrappers and subjected to proper storage (6 h at 4°C) or improper storage (72 h at 15°C) before preparation. The model had four unit operations (pathogen events): (i) preparation (contamination), (ii) cooking (death), (iii) serving (cross-contamination), and (iv) consumption (dose-response). Data for prevalence, number, and serotype of Salmonella on chicken parts were obtained by whole sample enrichment, real-time PCR. Improper storage increased (P < 0.05) prevalence of Salmonella on raw chicken parts from 10.6% (17 of 160) to 41.2% (66 of 160) and incidence of cross-contamination of cooked chicken from 10% (4 of 40) to 52.2% (24 of 46). Improper storage also increased (P < 0.05) the number (mean ± standard deviation) of Salmonella from 0.017 ± 0.030 to 3.51 ± 1.34 log per raw chicken part and from 0.048 ± 0.089 to 3.08 ± 1.50 log per cooked chicken part. The predominant serotypes isolated (n = 111) were Typhimurium (34.2%), Typhimurium var 5- (20.7%), Kentucky (12.6%), Enteritidis (11.7%), and Heidelberg (8.1%). When chicken was properly stored before preparation, the model predicted that risk of salmonellosis was low and sporadic with only six cases per 100 simulations of 10 chicken parts. However, when 0.1 to 1% of chickens were improperly stored before preparation, the model predicted that salmonellosis would increase (P < 0.05) linearly from a median of 7 (range, 1 to 15) to a median of 72 (range, 52 to 93) cases per 10 chicken parts. These results indicated that the flow pack wrapper provided a favorable environment for growth and spread of Salmonella within the package and that even when only a small percentage of packages were subjected to improper storage before preparation, the risk and size of an outbreak of salmonellosis from chicken parts increased significantly.

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“…Specifically, O stands for the probability/frequency of occurrence of the hazard whereas S represents the level of damage as a consequence of the hazard's occurrence. Therefore, the hazard analysis refers to the process of collecting and evaluating information on hazards associated with the food under consideration to look at the conditions that may cause hazards to be present or to increase, and to decide which hazards must be addressed into the HACCP plan (Oscar, 2012). Actually, listed hazards are so numerous that none food safety system can address all related potential problems.…”

Section: Introductionmentioning

confidence: 99%

Food safety risk analysis from the producers' perspective: prioritisation of production process stages by HACCP and TOPSIS

Certa

Enea

Galante

et al. 2018

IJMDM

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Prof. Certa's research interests are mainly focused on project management, multi-criteria analysis and maintenance optimization models. Mario Enea is full professor of Project Management, Industrial Plants Management and Applied Economics for Engineering at the University of Palermo. His research fields include production management, scheduling problems related to project management, optimal layout problems, environmental impact evaluation and waste management.

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Food Risk Analysis

Cited by 4 publications

References 11 publications

Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Risk of Salmonellosis from Chicken Parts Prepared from Whole Chickens Sold in Flow Pack Wrappers and Subjected to Temperature Abuse

Food safety risk analysis from the producers' perspective: prioritisation of production process stages by HACCP and TOPSIS

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