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Listeria monocytogenes risk assessment model for three ready-to-eat food categories in the EU

Authors: Pérez-Rodríguez, Fernando; Carrasco, Elena; Bover-Cid, Sara; Jofré, Anna; Valero, Antonio;

Listeria monocytogenes risk assessment model for three ready-to-eat food categories in the EU

Abstract

The Listeria monocytogenes risk assessment model allows the estimation of the number of listeriosis cases per year in the EU population as well as predicted risk for listeriosis per million servings from consumption of a meal containing each of the three ready-to-eat (RTE) food categories: heat-treated meat, gravad and smoked fish and soft and semi-soft cheese. For each food category, a specific risk model spreadsheet was built, in Excel (Microsoft, Redmond), using functions from @Risk software (Palisade ©, NY). The risk model Excel files for the above-mentioned RTE food categories were named as “Listeria_RiskModel_meat_v1.xlsm”, “Listeria_RiskModel_fish_v1.xlsm” and “Listeria_RiskModel_cheese_v1.xlsm”, respectively. In addition, an Excel Add-in, called Lis-RA, was developed with Visual Basic for Applications (VBA) based a customized Ribbon interface that allows users to load risk models, select scenarios and define model inputs and simulation settings. The software tool, contained in the file named as “Listeria_App_LisRA_v1.xlsm, is an easy and intuitive way for introducing, selecting data and options for listeriosis risk assessment model simulation. The application requires @Risk software installed and is optimized for Excel 2016 and @Risk 7.0 and 7.5. The user manual explains the structure and use of the spreadsheets developed in Excel and the main features of the Add-in Lis-RA.

Keywords

ready-to-eat food, http://aims.fao.org/aos/agrovoc/c_26553, http://aims.fao.org/aos/agrovoc/c_24119, http://aims.fao.org/aos/agrovoc/c_37932

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selected citations
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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).
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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.
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