Evidence map›Paper›PMID 39712916›Full record

ArticleEFSA journal. European Food Safety Authority2024

Combined stochastic modelling of pathogenic and spoilage microorganisms.

Nikola Maciejewska, Constantine-Richard Stefanou, Leonardos Stathas, Konstantinos Koutsoumanis

Abstract read
In one paragraph

Article in EFSA journal. European Food Safety Authority, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Probabilistic MIC modelling for AMR risk assessment.EFSA journal. European Food Safety Authority · 2025
    Article
  3. Review
  4. Combined stochastic modelling of pathogenic and spoilage microorganisms.EFSA journal. European Food Safety Authority · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nikola MaciejewskaDepartment of Food Quality, Prof. Waclaw Dabrowski Institute of Agriculture and Food Biotechnology State Research Institute Lodz Poland.
Constantine-Richard StefanouLaboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece.
Leonardos StathasLaboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece.
Konstantinos KoutsoumanisLaboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Faculty of Agriculture, Forestry and Natural Environment Aristotle University of Thessaloniki Thessaloniki Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative microbiological risk assessment (QMRA) of pathogens in food safety is well established, but steps are being taken to expand this methodology to food spoilage. Parallels can be drawn between the steps involved in a QMRA for pathogens and its application to specific spoilage organisms (SSO). During hazard characterisation for pathogens, the appropriate dose-response model is used to link the hazard level to the health outcome by estimating the probability of illness, resulting from the ingestion of a certain dose of the hazard. The dose-response model, in the case of food spoilage, may be translated into a spoilage-response relationship linking the spoilage-level with the probability the consumer will discard the food and not consume it. Such models are developed with sensory testing, assessing consumers sensitivity to microbial spoilage quality defects and correlating them to the SSO concentration. Ignoring food spoilage before the stated expiration date can lead to the final health risk being overestimated, since cases in which the food item poses a real risk to the consumer but is not consumed due to perceived spoilage are not excluded. Plenty of risk assessments have been carried out for pathogens in different RTE foods. What is missing is the integration of the two approaches into a single model that can estimate the risk of illness, factoring in the variability of consumer responses to spoilage. The spoilage-response relationship was combined with a stochastic modelling approach for lactic acid bacteria (LAB) and

Indexed as

deli meatslactic acid bacteriaListeria monocytogeneslisteriosispredictive microbiologyQMRArisk assessmentspoilage

Identifiers

PMID39712916
PMCPMC11659746

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.