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Quantitative Risk Assessment of Listeria monocytogenes in Foods

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A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Microbiology".

Deadline for manuscript submissions: 30 October 2024 | Viewed by 6330

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Special Issue Editor

Prof. Dr. Michel Federighi

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Guest Editor

1. EnvA, 7 Avenue du Général de Gaulle, F-94700 Maisons-Alfort, France
2. INRAe, UMR1014 SECALIM, F-44307 Nantes, France
Interests: risk analysis; food safety; biostatistics; veterinary public health
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Special Issue Information

Dear Colleagues,

The scope of this Special Issue ‘Quantitative Risk Assessment of Listeria monocytogenes in Foods’ is twofold: (1) to present a critical analysis of the existing human listeriosis quantitative risk assessment models conducted on milk and dairy products, produce, seafood and meat product, highlighting common results from intervention strategies, despite the unavoidable differences in model scopes and assumptions; and (2) to present new quantitative risk assessment models of longer food chain scope, in the light of new data and approaches, to control listeriosis linked to specific foods such as frozen vegetables, cantaloupe and ready-to-eat seafood.

In response to a request by the Codex Committee on Food Hygiene (CCFH) at its 52nd session, formal risk assessment models were developed by the Joint FAO/WHO Expert Meeting on Microbiological Risk Assessment of Listeria monocytogenes in Foods: Part 1 (FAO HQ, Rome, Italy: 24–28 October 2022), taking into account the effects of agrifood practices, climate change and the latent possibility of cross-contamination along the food chain. Programmed models were subsequently tested and revised at the Joint FAO/WHO Expert Meeting on Microbiological Risk Assessment of Listeria monocytogenes in Foods, Part 2: Risk Assessment Models (WHO HQ, Geneva, Switzerland: 29 May–2 June 2023).

Prof. Dr. Michel Federighi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

listeriosis
cantaloupe
produce
seafood
ready-to-eat
dose–response
simulation models
intervention strategies

Published Papers (5 papers)

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Research

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15 pages, 749 KiB

Open AccessArticle

Updated Parameters for Listeria monocytogenes Dose–Response Model Considering Pathogen Virulence and Age and Sex of Consumer

by Régis Pouillot, Andreas Kiermeier, Laurent Guillier, Vasco Cadavez and Moez Sanaa

Foods 2024, 13(5), 751; https://0-doi-org.brum.beds.ac.uk/10.3390/foods13050751 - 29 Feb 2024

Cited by 1 | Viewed by 824

Abstract

Better knowledge regarding the Listeria monocytogenes dose–response (DR) model is needed to refine the assessment of the risk of foodborne listeriosis. In 2018, the European Food Safety Agency (EFSA) derived a lognormal Poisson DR model for 14 different age–sex sub-groups, marginally to strain virulence. In the present study, new sets of parameters are developed by integrating the EFSA model for these sub-groups together with three classes of strain virulence characteristics (“less virulent”, “virulent”, and “more virulent”). Considering classes of virulence leads to estimated relative risks (RRs) of listeriosis following the ingestion of 1000 bacteria of “less virulent” vs. “more virulent” strains ranging from 21.6 to 24.1, depending on the sub-group. These relatively low RRs when compared with RRs linked to comorbidities described in the literature suggest that the influence of comorbidity on the occurrence of invasive listeriosis for a given exposure is much more important than the influence of the virulence of the strains. The updated model parameters allow better prediction of the risk of invasive listeriosis across a population of interest, provided the necessary data on population demographics and the proportional contribution of strain virulence classes in food products of interest are available. An R package is made available to facilitate the use of these dose–response models. Full article

(This article belongs to the Special Issue Quantitative Risk Assessment of Listeria monocytogenes in Foods)

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Review

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19 pages, 327 KiB

Open AccessReview

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Produce

by Ursula Gonzales-Barron, Vasco Cadavez, Juliana De Oliveira Mota, Laurent Guillier and Moez Sanaa

Foods 2024, 13(7), 1111; https://0-doi-org.brum.beds.ac.uk/10.3390/foods13071111 - 04 Apr 2024

Viewed by 1000

Abstract

A review of quantitative risk assessment (QRA) models of Listeria monocytogenes in produce was carried out, with the objective of appraising and contrasting the effectiveness of the control strategies placed along the food chains. Despite nine of the thirteen QRA models recovered being focused on fresh or RTE leafy greens, none of them represented important factors or sources of contamination in the primary production, such as the type of cultivation, water, fertilisers or irrigation method/practices. Cross-contamination at processing and during consumer’s handling was modelled using transfer rates, which were shown to moderately drive the final risk of listeriosis, therefore highlighting the importance of accurately representing the transfer coefficient parameters. Many QRA models coincided in the fact that temperature fluctuations at retail or temperature abuse at home were key factors contributing to increasing the risk of listeriosis. In addition to a primary module that could help assess current on-farm practices and potential control measures, future QRA models for minimally processed produce should also contain a refined sanitisation module able to estimate the effectiveness of various sanitisers as a function of type, concentration and exposure time. Finally, L. monocytogenes growth in the products down the supply chain should be estimated by using realistic time–temperature trajectories, and validated microbial kinetic parameters, both of them currently available in the literature. Full article

(This article belongs to the Special Issue Quantitative Risk Assessment of Listeria monocytogenes in Foods)

18 pages, 302 KiB

Open AccessReview

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Seafood

by Ursula Gonzales-Barron, Vasco Cadavez, Juliana De Oliveira Mota, Laurent Guillier and Moez Sanaa

Foods 2024, 13(5), 716; https://0-doi-org.brum.beds.ac.uk/10.3390/foods13050716 - 26 Feb 2024

Viewed by 792

Abstract

Invasive listeriosis, due to its severe nature in susceptible populations, has been the focus of many quantitative risk assessment (QRA) models aiming to provide a valuable guide in future risk management efforts. A review of the published QRA models of Listeria monocytogenes in seafood was performed, with the objective of appraising the effectiveness of the control strategies at different points along the food chain. It is worth noting, however, that the outcomes of a QRA model are context-specific, and influenced by the country and target population, the assumptions that are employed, and the model architecture itself. Studies containing QRA models were retrieved through a literature search using properly connected keywords on Scopus and PubMed^®. All 13 QRA models that were recovered were of short scope, covering, at most, the period from the end of processing to consumption; the majority (85%) focused on smoked or gravad fish. Since the modelled pathways commenced with the packaged product, none of the QRA models addressed cross-contamination events. Many models agreed that keeping the product’s temperature at 4.0–4.5 °C leads to greater reductions in the final risk of listeriosis than reducing the shelf life by one week and that the effectiveness of both measures can be surpassed by reducing the initial occurrence of L. monocytogenes in the product (at the end of processing). It is, therefore, necessary that future QRA models for RTE seafood contain a processing module that can provide insight into intervention strategies that can retard L. monocytogenes’ growth, such as the use of bacteriocins, ad hoc starter cultures and/or organic acids, and other strategies seeking to reduce cross-contamination at the facilities, such as stringent controls for sanitation procedures. Since risk estimates were shown to be moderately driven by growth kinetic parameters, namely, the exponential growth rate, the minimum temperature for growth, and the maximum population density, further work is needed to reduce uncertainties. Full article

(This article belongs to the Special Issue Quantitative Risk Assessment of Listeria monocytogenes in Foods)

21 pages, 318 KiB

Open AccessEditor’s ChoiceReview

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Meat and Meat Products

by Ursula Gonzales-Barron, Vasco Cadavez, Juliana De Oliveira Mota, Laurent Guillier and Moez Sanaa

Foods 2024, 13(3), 359; https://0-doi-org.brum.beds.ac.uk/10.3390/foods13030359 - 23 Jan 2024

Viewed by 1673

Abstract

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in meat and meat products was performed, with the objective of appraising the intervention strategies deemed suitable for implementation along the food chain as well as their relative effectiveness. A systematic review retrieved 23 QRA models; most of them (87%) focused on ready-to-eat meat products and the majority (78%) also covered short supply chains (end processing/retail to consumption, or consumption only). The processing-to-table scope was the choice of models for processed meats such as chorizo, bulk-cooked meat, fermented sausage and dry-cured pork, in which the effects of processing were simulated. Sensitivity analysis demonstrated the importance of obtaining accurate estimates for lag time, growth rate and maximum microbial density, in particular when affected by growth inhibitors and lactic acid bacteria. In the case of deli meats, QRA models showed that delicatessen meats sliced at retail were associated with a higher risk of listeriosis than manufacture pre-packed deli meats. Many models converged on the fact that (1) controlling cold storage temperature led to greater reductions in the final risk than decreasing the time to consumption and, furthermore, that (2) lower numbers and less prevalence of L. monocytogenes at the end of processing were far more effective than keeping low temperatures and/or short times during retail and/or home storage. Therefore, future listeriosis QRA models for meat products should encompass a processing module in order to assess the intervention strategies that lead to lower numbers and prevalence, such as the use of bio-preservation and novel technologies. Future models should be built upon accurate microbial kinetic parameters, and should realistically represent cross-contamination events along the food chain. Full article

(This article belongs to the Special Issue Quantitative Risk Assessment of Listeria monocytogenes in Foods)

19 pages, 514 KiB

Open AccessReview

A Critical Review of Risk Assessment Models for Listeria monocytogenes in Dairy Products

by Ursula Gonzales-Barron, Vasco Cadavez, Laurent Guillier and Moez Sanaa

Foods 2023, 12(24), 4436; https://0-doi-org.brum.beds.ac.uk/10.3390/foods12244436 - 11 Dec 2023

Cited by 3 | Viewed by 1588

Abstract

A review of the published quantitative risk assessment (QRA) models of L. monocytogenes in dairy products was undertaken in order to identify and appraise the relative effectiveness of control measures and intervention strategies implemented at primary production, processing, retail, and consumer practices. A systematic literature search retrieved 18 QRA models, most of them (9) investigated raw and pasteurized milk cheeses, with the majority covering long supply chains (4 farm-to-table and 3 processing-to-table scopes). On-farm contamination sources, either from shedding animals or from the broad environment, have been demonstrated by different QRA models to impact the risk of listeriosis, in particular for raw milk cheeses. Through scenarios and sensitivity analysis, QRA models demonstrated the importance of the modeled growth rate and lag phase duration and showed that the risk contribution of consumers’ practices is greater than in retail conditions. Storage temperature was proven to be more determinant of the final risk than storage time. Despite the pathogen’s known ability to reside in damp spots or niches, re-contamination and/or cross-contamination were modeled in only two QRA studies. Future QRA models in dairy products should entail the full farm-to-table scope, should represent cross-contamination and the use of novel technologies, and should estimate L. monocytogenes growth more accurately by means of better-informed kinetic parameters and realistic time–temperature trajectories. Full article

(This article belongs to the Special Issue Quantitative Risk Assessment of Listeria monocytogenes in Foods)

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