Using Risk Analysis for Microbial Food Safety Regulatory Decision Making

Dennis, Sherri; Kause, Janell; Losikoff, Mary; Engeljohn, Daniel; Buchanan, Robert L.

doi:10.1128/9781555815752.ch5

Cited by 6 publications

(3 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The risk question determines the QMRA´s objective by defining the hazard, the product or matrix, the relevant steps (exposure scenario) and the target population (population group); all forming the base for the construction of the QMRA model structure (Figure 1). The context, complexity and purpose of the risk question define the scope, which may or may not involve a full risk assessment, the methods and relevant tools (Dennis et al, 2008).…”

Section: 1terms and Concepts (Phase 1)mentioning

confidence: 99%

“…The reviewing process aims to assess the quality of a risk assessment, checking all the assumptions, technicalities, logic of the model, data and model selection, etc. It can be accomplished as a multistep process involving one or more technical reviews, regulatory reviews and independent formal peer review (Dennis et al, 2008). …”

Section: Qmra Modelsmentioning

confidence: 99%

“…Can be a multistep review process involving one or more technical reviews, regulatory reviews and independent formal peer review (Dennis et al, 2008).…”

Section: A C C E P T E D Mmentioning

confidence: 99%

See 2 more Smart Citations

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

View full text Add to dashboard Cite

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.

show abstract

Section: 1terms and Concepts (Phase 1)mentioning

confidence: 99%

Section: Qmra Modelsmentioning

confidence: 99%