Literature DB >> 9709243

The application of quantitative risk assessment to microbial food safety.

D J Vose1.   

Abstract

Quantitative risk assessment (QRA) is rapidly accumulating recognition as the most practical method for assessing the risks associated with microbial contamination of foodstuffs. These risk analyses are most commonly developed in commercial computer spreadsheet applications, combined with Monte Carlo simulation add-ins that enable probability distributions to be inserted into a spreadsheet. If a suitable model structure can be defined and all of the variables within that model reasonably quantified, a QRA will demonstrate the sensitivity of the severity of the risk to each stage in the risk-assessment model. It can therefore provide guidance for the selection of appropriate risk-reduction measures and a quantitative assessment of the benefits and costs of these proposed measures. However, very few reports explaining QRA models have been submitted for publication in this area. There is, therefore, little guidance available to those who intend to embark on a full microbial QRA. This paper looks at a number of modeling techniques that can help produce more realistic and accurate Monte Carlo simulation models. The use and limitations of several distributions important to microbial risk assessment are explained. Some simple techniques specific to Monte Carlo simulation modelling of microbial risks using spreadsheets are also offered which will help the analyst more realistically reflect the uncertain nature of the scenarios being modeled. simulation, food safety.

Mesh:

Year:  1998        PMID: 9709243     DOI: 10.4315/0362-028x-61.5.640

Source DB:  PubMed          Journal:  J Food Prot        ISSN: 0362-028X            Impact factor:   2.077


  15 in total

1.  Expanded Fermi solution for estimating the survival of ingested pathogenic and probiotic microbial cells and spores.

Authors:  Micha Peleg; Mark D Normand; Joseph Horowitz; Maria G Corradini
Journal:  Appl Environ Microbiol       Date:  2010-11-05       Impact factor: 4.792

Review 2.  Microbiological quantitative risk assessment and food safety: an update.

Authors:  V Giaccone; M Ferri
Journal:  Vet Res Commun       Date:  2005-08       Impact factor: 2.459

3.  Estimation of Staphylococcus aureus growth parameters from turbidity data: characterization of strain variation and comparison of methods.

Authors:  R Lindqvist
Journal:  Appl Environ Microbiol       Date:  2006-07       Impact factor: 4.792

4.  Estimation of microbial contamination of food from prevalence and concentration data: application to Listeria monocytogenes in fresh vegetables.

Authors:  Amélie Crépet; Isabelle Albert; Catherine Dervin; Frédéric Carlin
Journal:  Appl Environ Microbiol       Date:  2006-11-10       Impact factor: 4.792

5.  Predictive modeling and probabilistic risk assessment of Clostridium perfringens in hamburgers and sandwiches.

Authors:  Yun Hui Choi; Jin Hwa Park; Mi Seon Kang; Yohan Yoon; Sang-do Ha; Hyun Jung Kim
Journal:  Food Sci Biotechnol       Date:  2021-11-23       Impact factor: 2.391

6.  Quantitative Microbial Risk Assessment for Campylobacter spp. on Ham in Korea.

Authors:  Jeeyeon Lee; Jimyeong Ha; Sejeong Kim; Heeyoung Lee; Soomin Lee; Yohan Yoon
Journal:  Korean J Food Sci Anim Resour       Date:  2015-10-31       Impact factor: 2.622

7.  A quantitative risk assessment approach for mosquito-borne diseases: malaria re-emergence in southern France.

Authors:  Nicolas Ponçon; Annelise Tran; Céline Toty; Adrian Jf Luty; Didier Fontenille
Journal:  Malar J       Date:  2008-08-01       Impact factor: 2.979

8.  Waterborne microbial risk assessment: a population-based dose-response function for Giardia spp. (E.MI.R.A study).

Authors:  D Zmirou-Navier; L Gofti-Laroche; Ph Hartemann
Journal:  BMC Public Health       Date:  2006-05-03       Impact factor: 3.295

9.  Quantitative Microbial Risk Assessment for Clostridium perfringens in Natural and Processed Cheeses.

Authors:  Heeyoung Lee; Soomin Lee; Sejeong Kim; Jeeyeon Lee; Jimyeong Ha; Yohan Yoon
Journal:  Asian-Australas J Anim Sci       Date:  2016-02-12       Impact factor: 2.509

10.  Comparison of the Effects of Environmental Parameters on the Growth Variability of Vibrio parahaemolyticus Coupled with Strain Sources and Genotypes Analyses.

Authors:  Bingxuan Liu; Haiquan Liu; Yingjie Pan; Jing Xie; Yong Zhao
Journal:  Front Microbiol       Date:  2016-06-23       Impact factor: 5.640

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