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Food and Ecological Systems Modelling Journal
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Article . 2024
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Quantitative risk assessment of Haemolytic and Uremic Syndrome (HUS) from consumption of raw milk soft cheese

Authors: Subhasish Basak; Janushan Christy; Laurent Guillier; Frederique Audiat-Perrin; Moez Sanaa; Fanny Tenenhaus-Aziza; Julien Bect; +1 Authors

Quantitative risk assessment of Haemolytic and Uremic Syndrome (HUS) from consumption of raw milk soft cheese

Abstract

The aim of this quantitative risk assessment model is to estimate the risk of Haemolytic Uremic Syndrome (HUS) caused by Shiga-toxin producing Escherichia coli (STEC) in raw milk soft cheese and explore intervention strategies to minimise this risk. Building upon previous work from literature, the model considers microbial contamination of raw milk at the farm level, as well as STEC growth and survival during cheese production, ripening and storage, along with intervention strategies in both pre- and post-harvest scenarios. It allows for the assessment of intervention steps at the farm level or during cheese production. Besides estimating the risk of HUS, it also assesses the production losses associated with interventions.

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Keywords

raw milk soft cheese, R programming language, E. coli, QMRA model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold