The qualified presumption of safety (QPS) was developed to provide a safety pre‐assessment within EFSA for microorganisms. Strains belonging to QPS taxonomic units (TUs) still require an assessment ...based on a specific data package, but QPS status facilitates fast track evaluation. QPS TUs are unambiguously defined biological agents assessed for the body of knowledge, their safety and their end use. Safety concerns are, where possible, to be confirmed at strain or product level, and reflected as ‘qualifications’. Qualifications need to be evaluated at strain level by the respective EFSA units. The lowest QPS TU is the species level for bacteria, yeasts and protists/algae, and the family for viruses. The QPS concept is also applicable to genetically modified microorganisms used for production purposes if the recipient strain qualifies for the QPS status, and if the genetic modification does not indicate a concern. Based on the actual body of knowledge and/or an ambiguous taxonomic position, the following TUs were excluded from the QPS assessment: filamentous fungi, oomycetes, streptomycetes, Enterococcus faecium, Escherichia coli and bacteriophages. The list of QPS‐recommended biological agents was reviewed and updated in the current opinion and therefore now becomes the valid list. For this update, reports on the safety of previously assessed microorganisms, including bacteria, yeasts and viruses (the latter only when used for plant protection purposes) were reviewed, following an Extensive Literature Search strategy. All TUs previously recommended for 2016 QPS list had their status reconfirmed as well as their qualifications. The TUs related to the new notifications received since the 2016 QPS opinion was periodically evaluated for QPS status in the Statements of the BIOHAZ Panel, and the QPS list was also periodically updated. In total, 14 new TUs received a QPS status between 2017 and 2019: three yeasts, eight bacteria and three algae/protists.
Food safety criteria for Listeria monocytogenes in ready‐to‐eat (RTE) foods have been applied from 2006 onwards (Commission Regulation (EC) 2073/2005). Still, human invasive listeriosis was reported ...to increase over the period 2009–2013 in the European Union and European Economic Area (EU/EEA). Time series analysis for the 2008–2015 period in the EU/EEA indicated an increasing trend of the monthly notified incidence rate of confirmed human invasive listeriosis of the over 75 age groups and female age group between 25 and 44 years old (probably related to pregnancies). A conceptual model was used to identify factors in the food chain as potential drivers for L. monocytogenes contamination of RTE foods and listeriosis. Factors were related to the host (i. population size of the elderly and/or susceptible people; ii. underlying condition rate), the food (iii. L. monocytogenes prevalence in RTE food at retail; iv. L. monocytogenes concentration in RTE food at retail; v. storage conditions after retail; vi. consumption), the national surveillance systems (vii. improved surveillance), and/or the bacterium (viii. virulence). Factors considered likely to be responsible for the increasing trend in cases are the increased population size of the elderly and susceptible population except for the 25–44 female age group. For the increased incidence rates and cases, the likely factor is the increased proportion of susceptible persons in the age groups over 45 years old for both genders. Quantitative modelling suggests that more than 90% of invasive listeriosis is caused by ingestion of RTE food containing > 2,000 colony forming units (CFU)/g, and that one‐third of cases are due to growth in the consumer phase. Awareness should be increased among stakeholders, especially in relation to susceptible risk groups. Innovative methodologies including whole genome sequencing (WGS) for strain identification and monitoring of trends are recommended.
This publication is linked to the following EFSA Supporting Publications article: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2018.EN-1352/full
Animal and bait poisoning data for northwest Italy collected between 2012 and 2017 were described and analyzed to estimate the risk of exposure to hazardous substances by animals. In about 4% of ...animals necropsied (n = 356/9512), the cause of death was poisoning and domestic pets (9.5%) and synanthropic animals (12.2%) appear to be the most involved. Furthermore, 294 out of 728 baits (40.4%) were positive for toxic substances and/or inert hazardous material.
Application of a mixed-effects Poisson regression model and local cluster analysis evidenced increased risk of exposure to poisoning with altimetry (>600 m.a.s.l.) and municipality (PR = 1.6, 95%CI 1.2–2.1 for poisoning, PR = 2.2, 95%CI 1.2–4.2 for poisoning by insecticides and PR = 2.9, 95%CI 1.4–6.2 for poisoning by metaldehyde). Since the mountainous areas in the region are mostly devoted to pasture and extensive farming, the high frequency of animal and bait poisoning events may be related to farmers' need to protect their livestock and crops against foxes, wolves, rodents or wild boars. Summarizing, the type of land use and context may influence the frequency and type of toxin chosen to kill animals considered a nuisance for hunting, farming, agriculture and apiculture. Despite bans and limitations, the use of harmful substances is not perceived as an environmental threat but rather as routine pest control.
Animal and bait poisoning constitute a public health concern because it is potentially harmful to humans and the environment. Our findings may inform risk communication strategies, as well as prevention and control measures for the reduction of illegal and non-targeted species poisoning.
Display omitted
•294 baits and 356 animals were positive for poisoning from 2012 to 2017.•More than half of detected insecticides were restricted substances.•Frequency of pesticides classes is influenced by different risk factors.•An increased risk associated with altimetry and municipality was detected.•Specific preventing measures and risk communication are needed in high risk areas.
The provisional molecular approach, proposed by EFSA in 2013, for the pathogenicity assessment of Shiga toxin‐producing Escherichia coli (STEC) has been reviewed. Analysis of the confirmed reported ...human STEC infections in the EU/EEA (2012–2017) demonstrated that isolates positive for any of the reported Shiga toxin (Stx) subtypes (and encoding stx gene subtypes) may be associated with severe illness (defined as bloody diarrhoea (BD), haemolytic uraemic syndrome (HUS) and/or hospitalisation). Although strains positive for stx2a gene showed the highest rates, strains with all other stx subtypes, or combinations thereof, were also associated with at least one human case with a severe clinical outcome. Serogroup cannot be used as a predictor of clinical outcome and the presence of the intimin gene (eae) is not essential for severe illness. These findings are supported by the published literature, a review of which suggested there was no single or combination of virulence markers associated exclusively with severe illness. Based on available evidence, it was concluded that all STEC strains are pathogenic in humans, capable of causing at least diarrhoea and that all STEC subtypes may be associated with severe illness. Source attribution analysis, based on ‘strong evidence’ outbreak data in the EU/EEA (2012–2017), suggests that ‘bovine meat and products thereof’, ‘milk and dairy products’, ‘tap water including well water’ and ‘vegetables, fruit and products thereof’ are the main sources of STEC infections in the EU/EEA, but a ranking between these categories cannot be made as the data are insufficient. Other food commodities are also potentially associated with STEC infections but rank lower. Data gaps are identified, and are primarily caused by the lack of harmonisation in sampling strategies, sampling methods, detection and characterisation methods, data collation and reporting within the EU.
The role of food‐producing environments in the emergence and spread of antimicrobial resistance (AMR) in EU plant‐based food production, terrestrial animals (poultry, cattle and pigs) and aquaculture ...was assessed. Among the various sources and transmission routes identified, fertilisers of faecal origin, irrigation and surface water for plant‐based food and water for aquaculture were considered of major importance. For terrestrial animal production, potential sources consist of feed, humans, water, air/dust, soil, wildlife, rodents, arthropods and equipment. Among those, evidence was found for introduction with feed and humans, for the other sources, the importance could not be assessed. Several ARB of highest priority for public health, such as carbapenem or extended‐spectrum cephalosporin and/or fluoroquinolone‐resistant Enterobacterales (including Salmonella enterica), fluoroquinolone‐resistant Campylobacter spp., methicillin‐resistant Staphylococcus aureus and glycopeptide‐resistant Enterococcus faecium and E. faecalis were identified. Among highest priority ARGs blaCTX‐M, blaVIM, blaNDM, blaOXA‐48-like, blaOXA‐23, mcr, armA, vanA, cfr and optrA were reported. These highest priority bacteria and genes were identified in different sources, at primary and post‐harvest level, particularly faeces/manure, soil and water. For all sectors, reducing the occurrence of faecal microbial contamination of fertilisers, water, feed and the production environment and minimising persistence/recycling of ARB within animal production facilities is a priority. Proper implementation of good hygiene practices, biosecurity and food safety management systems is very important. Potential AMR‐specific interventions are in the early stages of development. Many data gaps relating to sources and relevance of transmission routes, diversity of ARB and ARGs, effectiveness of mitigation measures were identified. Representative epidemiological and attribution studies on AMR and its effective control in food production environments at EU level, linked to One Health and environmental initiatives, are urgently required.
Extra virgin olive oil is the highest quality olive oil mainly due to its beneficial constituents and nutritional properties. However, olive oil adulteration is a common fraudulent practice by ...deliberate mislabelling of less expensive oil categories and admixing expensive olive oils with low oils. To protect consumers from such commercial frauds, an easy and fast method to detect the real composition of oil is needed. For this study we used direct sampling analysis (DSA) coupled with a high-resolution mass spectrometer (AxION2 TOF Perkin Elmer) to analyse the fatty acid composition of three types of edible oil: extra virgin olive oil, refined olive oil and seed oil (EVOO, ROO, and SO respectively) to find a marker that could distinguish between them. Good precision in repeatability and reproducibility (RSD% < 15%) was obtained. The fatty acid ratio between the oleic acid/oleic acid dimer was able to distinguish EVOO from the other two types of oil, while the ratio between linoleic and oleic acid was found to discriminate refined oil from seed oil. The development of an easy, fast and cost-effective method can help to limit commercial frauds, increase the number of controlled samples, and enhance food control along the commercial chain.
The qualified presumption of safety (QPS) provides a generic pre‐assessment of the safety of microorganisms intended for use in the food or feed chains, to support the work of EFSA's Scientific ...Panels. QPS assessment allows a fast track evaluation of strains belonging to QPS taxonomic units (TUs): species for bacteria, yeast, fungi, protists/microalgae and families for viruses. QPS TUs are assessed for their body of knowledge and safety. Safety concerns related to a QPS TU are reflected, when possible, as ‘qualifications’, which should be tested at strain and/or product level. Based on the possession of potentially harmful traits by some strains, filamentous fungi, bacteriophages, oomycetes, streptomycetes, Enterococcus faecium, Escherichia coli and Clostridium butyricum are excluded from the QPS assessment. Between October 2019 and September 2022, 323 notifications of TUs were received, 217 related to feed additives, 54 to food enzymes, food additives and flavourings, 14 to plant protection products and 38 to novel foods. The list of QPS‐recommended TUs is reviewed every 6 months following an extensive literature search strategy. Only sporadic infections with a few QPS status TUs in immunosuppressed individuals were identified and the assessment did not change the QPS status of these TUs. The QPS list has been updated in relation to the most recent taxonomic insights and the qualifications were revised and streamlined. The qualification ‘absence of aminoglycoside production ability’ was withdrawn for Bacillus velezensis. Six new TUs received the QPS status: Bacillus paralicheniformis with the qualification ‘absence of toxigenic activity’ and ‘absence of bacitracin production ability’; Bacillus circulans with the qualifications for ‘production purposes only’ and ‘absence of cytotoxic activity’; Haematococcus lacustris (synonym Haematococcus pluvialis) and Ogataea polymorpha, both with the qualification ‘for production purposes only’; Lactiplantibacillus argentoratensis; Geobacillus thermodenitrificans with the qualification ‘absence of toxigenic activity’.
Qualified presumption of safety (QPS) was developed to provide a generic safety evaluation for biological agents to support EFSA's Scientific Panels. The taxonomic identity, body of knowledge, safety ...concerns and antimicrobial resistance are assessed. Safety concerns identified for a taxonomic unit (TU) are where possible to be confirmed at strain or product level, reflected by ‘qualifications’. No new information was found that would change the previously recommended QPS TUs and their qualifications. The list of microorganisms notified to EFSA was updated with 54 biological agents, received between April and September 2019; 23 already had QPS status, 14 were excluded from the QPS exercise (7 filamentous fungi, 6 Escherichia coli, Sphingomonas paucimobilis which was already evaluated). Seventeen, corresponding to 16 TUs, were evaluated for possible QPS status, fourteen of these for the first time, and Protaminobacter rubrum, evaluated previously, was excluded because it is not a valid species. Eight TUs are recommended for QPS status. Lactobacillus parafarraginis and Zygosaccharomyces rouxii are recommended to be included in the QPS list. Parageobacillus thermoglucosidasius and Paenibacillus illinoisensis can be recommended for the QPS list with the qualification ‘for production purposes only’ and absence of toxigenic potential. Bacillus velezensis can be recommended for the QPS list with the qualifications; the absence of toxigenic potential and the absence of aminoglycoside production, including the genes encoding this. Cupriavidus necator, Aurantiochytrium limacinum and Tetraselmis chuii can be recommended for the QPS list with the qualification; for production purposes only. Pantoea ananatis is not recommended for the QPS list due to lack of body of knowledge in relation to its pathogenicity potential for plants. Corynebacterium stationis, Hamamotoa singularis, Rhodococcus aetherivorans and Rhodococcus ruber cannot be recommended for the QPS list due to lack of body of knowledge. Kodamaea ohmeri cannot be recommended for the QPS list due to safety concerns.
Salmonellosis, one of the most common foodborne infections in Europe, is monitored by food safety surveillance programmes, resulting in the generation of extensive databases. By leveraging tree-based ...machine learning (ML) algorithms, we exploited data from food safety audits to predict spatiotemporal patterns of salmonellosis in northwestern Italy. Data on human cases confirmed in 2015-2018 (n = 1969) and food surveillance data collected in 2014-2018 were used to develop ML algorithms. We integrated the monthly municipal human incidence with 27 potential predictors, including the observed prevalence of Salmonella in food. We applied the tree regression, random forest and gradient boosting algorithms considering different scenarios and evaluated their predictivity in terms of the mean absolute percentage error (MAPE) and R.sup.2. Using a similar dataset from the year 2019, spatiotemporal predictions and their relative sensitivities and specificities were obtained. Random forest and gradient boosting (R.sup.2 = 0.55, MAPE = 7.5%) outperformed the tree regression algorithm (R.sup.2 = 0.42, MAPE = 8.8%). Salmonella prevalence in food; spatial features; and monitoring efforts in ready-to-eat milk, fruits and vegetables, and pig meat products contributed the most to the models' predictivity, reducing the variance by 90.5%. Conversely, the number of positive samples obtained for specific food matrices minimally influenced the predictions (2.9%). Spatiotemporal predictions for 2019 showed sensitivity and specificity levels of 46.5% (due to the lack of some infection hotspots) and 78.5%, respectively. This study demonstrates the added value of integrating data from human and veterinary health services to develop predictive models of human salmonellosis occurrence, providing early warnings useful for mitigating foodborne disease impacts on public health. Keywords: Supervised learning, decision tree algorithms, disease surveillance, food products, salmonellosis, transdisciplinarity
An increase in confirmed human salmonellosis cases in the EU after 2014 triggered investigation of contributory factors and control options in poultry production. Reconsideration of the five current ...target serovars for breeding hens showed that there is justification for retaining Salmonella Enteritidis, Salmonella Typhimurium (including monophasic variants) and Salmonella Infantis, while Salmonella Virchow and Salmonella Hadar could be replaced by Salmonella Kentucky and either Salmonella Heidelberg, Salmonella Thompson or a variable serovar in national prevalence targets. However, a target that incorporates all serovars is expected to be more effective as the most relevant serovars in breeding flocks vary between Member State (MS) and over time. Achievement of a 1% target for the current target serovars in laying hen flocks is estimated to be reduced by 254,400 CrI9598,540; 602,700 compared to the situation in 2016. This translates to a reduction of 53.4% CrI9539.1; 65.7 considering the layer‐associated human salmonellosis true cases and 6.2% considering the overall human salmonellosis true cases in the 23 MSs included in attribution modelling. A review of risk factors for Salmonella in laying hens revealed that overall evidence points to a lower occurrence in non‐cage compared to cage systems. A conclusion on the effect of outdoor access or impact of the shift from conventional to enriched cages could not be reached. A similar review for broiler chickens concluded that the evidence that outdoor access affects the occurrence of Salmonella is inconclusive. There is conclusive evidence that an increased stocking density, larger farms and stress result in increased occurrence, persistence and spread of Salmonella in laying hen flocks. Based on scientific evidence, an impact of Salmonella control programmes, apart from general hygiene procedures, on the prevalence of Campylobacter in broiler flocks at the holding and on broiler meat at the end of the slaughter process is not expected.