Latest developments in foodborne pathogen risk assessment

Membré, Jeanne‐Marie; Guillou, Sandrine

doi:10.1016/j.cofs.2016.04.011

Cited by 33 publications

(10 citation statements)

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“…Nevertheless, this harmonization of approach might face some difficulties due to methodological differences of each field. In microbiology, quantitative farm‐to‐fork risk assessment has been developed since the 1990s, the methodology is well shared among the scientific community (academics and authorities), a relatively large amount of data are available, and probabilistic models are mostly developed to take biological variability into account . Biological mechanisms are often known and allow developing mathematical dose responses characterizing the hazard (Fig.…”

Section: Discussionmentioning

confidence: 99%

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components

et al. 2017

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A probabilistic and interdisciplinary risk-benefit assessment (RBA) model integrating microbiological, nutritional, and chemical components was developed for infant milk, with the objective of predicting the health impact of different scenarios of consumption. Infant feeding is a particular concern of interest in RBA as breast milk and powder infant formula have both been associated with risks and benefits related to chemicals, bacteria, and nutrients, hence the model considers these three facets. Cronobacter sakazakii, dioxin-like polychlorinated biphenyls (dl-PCB), and docosahexaenoic acid (DHA) were three risk/benefit factors selected as key issues in microbiology, chemistry, and nutrition, respectively. The present model was probabilistic with variability and uncertainty separated using a second-order Monte Carlo simulation process. In this study, advantages and limitations of undertaking probabilistic and interdisciplinary RBA are discussed. In particular, the probabilistic technique was found to be powerful in dealing with missing data and to translate assumptions into quantitative inputs while taking uncertainty into account. In addition, separation of variability and uncertainty strengthened the interpretation of the model outputs by enabling better consideration and distinction of natural heterogeneity from lack of knowledge. Interdisciplinary RBA is necessary to give more structured conclusions and avoid contradictory messages to policymakers and also to consumers, leading to more decisive food recommendations. This assessment provides a conceptual development of the RBA methodology and is a robust basis on which to build upon.

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Section: Discussionmentioning

confidence: 99%

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components

et al. 2017

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“…The incorporation of omics technology into QMRA has been discussed for some time [30,31]. Most of the studies in this area have focused on the use of whole genome sequencing (WGS) in the hazard identification step of QMRA [3 ]. However, achievements in the exposure assessment step are still limited, and a rare example is the study by Njage and Buys [32] that includes the potential of gene transfer between strains into the exposure to Escherichia coli due to the consumption of lettuce.…”

Section: Recent Developments In the Qmramentioning

confidence: 99%

“…Since then, an increasing number of QMRA models are developed by scientists and risk assessment bodies for guiding risk management options [3 ].…”

Section: Recent Developments In the Qmramentioning

confidence: 99%

“…Therefore, the microbiological food safety community (including people working within food authorities, food industries, consultancy companies and food research institutes) has invested great research efforts in the fields of predictive microbial modelling [2 ] and quantitative microbial risk assessment (QMRA) [3 ]. This led to new technologies for obtaining and processing experimental data, open databases to compile and share data, new mathematical models, and software tools capable to generate and apply these models [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Towards transparent and consistent exchange of knowledge for improved microbiological food safety

Plaza‐Rodríguez

Haberbeck

Desvignes

et al. 2018

Current Opinion in Food Science

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“…data and mathematical models) and resources (e.g. software tools and databases), as well as to A C C E P T E D M A N U S C R I P T 5 integrate, evaluate and apply previously generated knowledge and resources (Membré and Guillou, 2016). The predictive microbiology (Koutsoumanis et al, 2016) and quantitative microbiology risk assessment (QMRA) (Membré and Guillou, 2016) communities have invested great efforts and time to develop a rich variety of this knowledge and resources (Tenenhaus-Aziza and Ellouze, 2015).…”

Section: Introductionmentioning

confidence: 99%

Harmonized terms, concepts and metadata for microbiological risk assessment models: The basis for knowledge integration and exchange

Haberbeck

Plaza‐Rodríguez

Desvignes

et al. 2018

Microbial Risk Analysis

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Harmonized terms, concepts and metadata for microbiological risk assessment models: the basis for knowledge integration and exchange, Microbial Risk Analysis (2018Analysis ( ), doi: 10.1016Analysis ( /j.mran.2018 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Author names and affiliations Leticia Corresponding authorsLaurent Guillier; Maarten Nauta; Matthias Filter Short Title or Running HeadHarmonization for microbiological risk assessment modelling AbstractIn the last decades the microbial food safety community has developed a variety of valuable knowledge (e.g., mathematical models and data) and resources (e.g., databases and software tools)in the areas of quantitative microbial risk assessment (QMRA) and predictive microbiology.However, the reusability of this knowledge and the exchange of information between resources are currently difficult and time consuming. This problem has increased over time due to the lack of harmonized data format and rules for knowledge annotation. It includes the lack of a common understanding of basic terms and concepts and of a harmonized information exchange format to describe and annotate knowledge. The existence of ambiguities and inconsistencies in the use of terms and concepts in the QMRA and predictive microbial (PM) modelling necessitates a consensus on their refinement, which will allow a harmonized exchange of information within these areas.Therefore, this work aims to harmonize terms and concepts used in QMRA and PM modelling spanning from high level concepts as defined by Codex Alimentarius, Food and Agriculture Organization (FAO) and World Health Organization (WHO), up to terms generally used in statistics or data and software science. As a result, a harmonized schema for metadata that allows consistent annotation of data and models from these two domains is proposed. This metadata schema is also a . This platform will facilitate the sharing and execution of curated QMRA and PM models using the foundation of the proposed harmonized metadata schema and information exchange format. Furthermore, it will also provide access to related open source software libraries, converter tools and software-specific import and export functions that promote the adoption of FSK-ML by the microbial food safety community. In the future, these resources will hopefully promote both the knowledge reusability and the highquality information exchange between stakeholders within the areas of QMRA and PM modelling worldwide.

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Latest developments in foodborne pathogen risk assessment

Cited by 33 publications

References 61 publications

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components

Development and Application of a Probabilistic Risk–Benefit Assessment Model for Infant Feeding Integrating Microbiological, Nutritional, and Chemical Components

Towards transparent and consistent exchange of knowledge for improved microbiological food safety

Harmonized terms, concepts and metadata for microbiological risk assessment models: The basis for knowledge integration and exchange

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