Use of risk assessment and predictive microbiology in regulatory science related to the scientific opinions of the EFSA BIOHAZ Panel.

EFSA's Panel on Biological Hazards (BIOHAZ Panel) deals with questions on biological hazards relating to food safety and food-borne diseases. This covers food-borne zoonoses, transmissible spongiform encephalopathies, antimicrobial resistance, food microbiology, food hygiene, animal-by products, and associated waste management issues. The scientific assessments are diverse and frequently the development of new methodological approaches is required to deal with a mandate. Among the many risk factors, product characteristics (pH, water activity etc.), time and temperature of processing and storage along the food supply chain are highly relevant for assessing the biological risks. Therefore, predictive microbiology becomes an essential element of the assessments. Uncertainty analysis is incorporated in all BIOHAZ scientific assessments, to meet the general requirement for transparency. Assessments should clearly and unambiguously state what sources of uncertainty have been identified and their impact on the conclusions of the assessment. Four recent BIOHAZ Scientific Opinions are presented to illustrate the use of predictive modelling and quantitative microbial risk assessment principles in regulatory science. The Scientific Opinion on the guidance on date marking and related food information, gives a general overview on the use of predictive microbiology for shelf-life assessment. The Scientific Opinion on the efficacy and safety of high-pressure processing of food provides an example of inactivation modelling and compliance with performance criteria. The Scientific Opinion on the use of the so-called 'superchilling' technique for the transport of fresh fishery products illustrates the combination of heat transfer and microbial growth modelling. Finally, the Scientific Opinion on the delayed post-mortem inspection in ungulates, shows how variability and uncertainty, were quantitatively embedded in assessing the probability of Salmonella detection on carcasses, via stochastic modelling and expert knowledge elicitation.

Transmission of antimicrobial resistance (AMR) during animal transport.

The transmission of antimicrobial resistance (AMR) between food-producing animals (poultry, cattle and pigs) during short journeys (< 8 h) and long journeys (> 8 h) directed to other farms or to the slaughterhouse lairage (directly or with intermediate stops at assembly centres or control posts, mainly transported by road) was assessed. Among the identified risk factors contributing to the probability of transmission of antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs), the ones considered more important are the resistance status (presence of ARB/ARGs) of the animals pre-transport, increased faecal shedding, hygiene of the areas and vehicles, exposure to other animals carrying and/or shedding ARB/ARGs (especially between animals of different AMR loads and/or ARB/ARG types), exposure to contaminated lairage areas and duration of transport. There are nevertheless no data whereby differences between journeys shorter or longer than 8 h can be assessed. Strategies that would reduce the probability of AMR transmission, for all animal categories include minimising the duration of transport, proper cleaning and disinfection, appropriate transport planning, organising the transport in relation to AMR criteria (transport logistics), improving animal health and welfare and/or biosecurity immediately prior to and during transport, ensuring the thermal comfort of the animals and animal segregation. Most of the aforementioned measures have similar validity if applied at lairage, assembly centres and control posts. Data gaps relating to the risk factors and the effectiveness of mitigation measures have been identified, with consequent research needs in both the short and longer term listed. Quantification of the impact of animal transportation compared to the contribution of other stages of the food-production chain, and the interplay of duration with all risk factors on the transmission of ARB/ARGs during transport and journey breaks, were identified as urgent research needs.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 1: Methodology, general data gaps and uncertainties.

The European Commission requested EFSA to assess, in collaboration with EMA, the specific concentrations of antimicrobials resulting from cross-contamination in non-target feed for food-producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in microbial agents relevant for human and animal health, as well as the levels of the antimicrobials which could have a growth promotion/increase yield effect. The assessment was performed for 24 antimicrobial active substances, as specified in the mandate. This scientific opinion describes the methodology used, and the main associated data gaps and uncertainties. To estimate the antimicrobial levels in the non-target feed that would not result in emergence of, and/or selection for, resistance, a model was developed. This 'Feed Antimicrobial Resistance Selection Concentration' (FARSC) model is based on the minimal selective concentration (MSC), or the predicted MSC (PMSC) if MSC for the most susceptible bacterial species is unavailable, the fraction of antimicrobial dose available for exposure to microorganisms in the large intestine or rumen (considering pharmacokinetic parameters), the daily faecal output or rumen volume and the daily feed intake. Currently, lack of data prevents the establishment of PMSC and/or FARSC for several antimicrobials and animal species. To address growth promotion, data from an extensive literature search were used. Specific assessments of the different substances grouped by antimicrobial classes are addressed in separate scientific opinions. General conclusions and recommendations were made.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 2: Aminoglycosides/aminocyclitols: apramycin, paromomycin, neomycin and spectinomycin.

The specific concentrations of apramycin, paromomycin, neomycin and spectinomycin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for these antimicrobials, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for apramycin and neomycin, whilst for paromomycin and spectinomycin, no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these four antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 3: Amprolium.

The specific concentrations of amprolium in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC for amprolium, it was not possible to conclude the assessment. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of amprolium in feed that showed to have an effect on growth promotion/increased yield were reported. The lack of antibacterial activity at clinically relevant concentrations for amprolium suggests that further studies relating to bacterial resistance are not a priority.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 4: ß-Lactams: amoxicillin and penicillin V.

The specific concentrations of amoxicillin and penicillin V in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for amoxicillin, whilst for penicillin V no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these two antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 5: Lincosamides: lincomycin.

The specific concentrations of lincomycin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of lincomycin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for lincomycin.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 7: Amphenicols: florfenicol and thiamphenicol.

The specific concentrations of florfenicol and thiamphenicol in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for florfenicol was estimated. However, due to the lack of data, the calculation of the FARSC for thiamphenicol was not possible until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for florfenicol, whilst for thiamphenicol no suitable data for the assessment were available. Uncertainties and data gaps associated to the levels reported were addressed. For florfenicol, it was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC, whereas for thiamphenicol, the recommendation was to generate the data required to fill the gaps which prevented the FARSC calculation.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 6: Macrolides: tilmicosin, tylosin and tylvalosin.

The specific concentrations of tilmicosin, tylosin and tylvalosin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield, were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tilmicosin and tylosin, whilst for tylvalosin no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these three antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 8: Pleuromutilins: tiamulin and valnemulin.

The specific concentrations of tiamulin and valnemulin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tiamulin, while for valnemulin no suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these two antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 9: Polymyxins: colistin.

The specific concentrations of colistin in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data become available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels of colistin in feed that showed to have an effect on growth promotion/increased yield were reported. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed.Part 10: Quinolones: flumequine and oxolinic acid.

The specific concentrations of flumequine and oxolinic acid in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 11: Sulfonamides.

The specific concentrations of sulfonamides in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. However, due to the lack of data on the parameters required to calculate the FARSC, it was not possible to conclude the assessment until further experimental data are available. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were identified for three sulfonamides: sulfamethazine, sulfathiazole and sulfamerazine. It was recommended to carry out studies to generate the data that are required to fill the gaps which prevented the calculation of the FARSC for these antimicrobials.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 13: Diaminopyrimidines: trimethoprim.

The specific concentrations of trimethoprim in non-target feed for food-producing animals below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties, are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for trimethoprim was estimated. Uncertainties and data gaps associated to the levels reported were addressed. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. No suitable data for the assessment were available. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for trimethoprim.

Maximum levels of cross-contamination for 24 antimicrobial active substances in non-target feed. Part 12: Tetracyclines: tetracycline, chlortetracycline, oxytetracycline, and doxycycline.

The specific concentrations of tetracycline, chlortetracycline, oxytetracycline and doxycycline in non-target feed for food-producing animals, below which there would not be an effect on the emergence of, and/or selection for, resistance in bacteria relevant for human and animal health, as well as the specific antimicrobial concentrations in feed which have an effect in terms of growth promotion/increased yield were assessed by EFSA in collaboration with EMA. Details of the methodology used for this assessment, associated data gaps and uncertainties are presented in a separate document. To address antimicrobial resistance, the Feed Antimicrobial Resistance Selection Concentration (FARSC) model developed specifically for the assessment was applied. The FARSC for these four tetracyclines was estimated. To address growth promotion, data from scientific publications obtained from an extensive literature review were used. Levels in feed that showed to have an effect on growth promotion/increased yield were reported for tetracycline, chlortetracycline, oxytetracycline, whilst for doxycycline no suitable data for the assessment were available. Uncertainties and data gaps associated with the levels reported were addressed. It was recommended to perform further studies to supply more diverse and complete data related to the requirements for calculation of the FARSC for these antimicrobials.

Scientific report on the analysis of the 2-year compulsory intensified monitoring of atypical scrapie.

The European Commission asked EFSA whether the scientific data on the 2-year intensified monitoring in atypical scrapie (AS) outbreaks (2013-2020) provide any evidence on the contagiousness of AS, and whether they added any new knowledge on the epidemiology of AS. An ad hoc data set from intensified monitoring in 22 countries with index case/s of AS in sheep and/or goats (742 flocks from 20 countries, 76 herds from 11 countries) was analysed. No secondary cases were confirmed in goat herds, while 35 secondary cases were confirmed in 28 sheep flocks from eight countries. The results of the calculated design prevalence and of a model simulation indicated that the intensified monitoring had limited ability to detect AS, with no difference between countries with or without secondary cases. A regression model showed an increased, but not statistically significant, prevalence (adjusted by surveillance stream) of secondary cases in infected flocks compared with that of index cases in the non-infected flocks (general population). A simulation model of within-flock transmission, comparing a contagious (i.e. transmissible between animals under natural conditions) with a non-contagious scenario, produced a better fit of the observed data with the non-contagious scenario, in which each sheep in a flock had the same probability of developing AS in the first year of life. Based on the analyses performed, and considering uncertainties and data limitations, it was concluded that there is no new evidence that AS can be transmitted between animals under natural conditions, and it is considered more likely (subjective probability range 50-66%) that AS is a non-contagious, rather than a contagious disease. The analysis of the data of the EU intensified monitoring in atypical scrapie infected flocks/herds confirmed some of the known epidemiological features of AS but identified that major knowledge gaps still remain.

Role played by the environment in the emergence and spread of antimicrobial resistance (AMR) through the food chain.

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 bla CTX -M, bla VIM, bla NDM, bla OXA -48-like, bla OXA -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.

A neonatal cluster of novel coronavirus disease 2019: clinical management and considerations.

BACKGROUND: Lately, one of the major clinical and public health issues has been represented by Coronavirus disease of 2019 (COVID-19) during pregnancy and the risk of transmission of the infection from mother to child. Debate on perinatal management and postnatal care is still ongoing, principally questioning the option of the joint management of mother and child after birth and the safety of breastfeeding. According to the available reports, neonatal COVID-19 appears to have a horizontal transmission and seems to be paucisymptomatic or asymptomatic, compared to older age groups. The aim of this work is to describe a cluster of neonatal COVID-19 and discuss our experience, with reference to current evidence on postnatal care and perinatal management. METHODS: This is a retrospective observational case series of five mother-child dyads, who attended the Labor and Delivery Unit of a first-level hospital in Italy, in March 2020. Descriptive statistics for continuous variables consisted of number of observations, mean and the range of the minimum and maximum values. RESULTS: Five women and four neonates tested positive for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). In one case, the mother-child dyad was separated and the neonate remained negative on two consecutive tests. Two positive neonates developed symptoms, with a predominant involvement of the gastrointestinal tract. Blood tests were unremarkable, except for a single patient who developed mild neutropenia. No complications occurred. CONCLUSIONS: We agree that the decision on whether or not to separate a positive/suspected mother from her child should be made on an individual basis, taking into account the parent's will, clinical condition, hospital logistics and the local epidemiological situation. In conformity with literature, in our study, affected neonates were asymptomatic or paucisymptomatic. Despite these reassuring findings, a few cases of severe presentation in the neonatal population have been reported. Therefore, we agree on encouraging clinicians to monitor the neonates with a suspected or confirmed infection.

Advancing biological hazards risk assessment.

This paper focusses on biological hazards at the global level and considers the challenges to risk assessment (RA) from a One Health perspective. Two topics - vector-borne diseases (VBD) and antimicrobial resistance (AMR) - are used to illustrate the challenges ahead and to explore the opportunities that new methodologies such as next-generation sequencing can offer. Globalisation brings complexity and introduces drivers for infectious diseases. Cooperation and the application of an integrated RA approach - one that takes into consideration food farming and production systems including social and environmental factors - are recommended. Also needed are methodologies to identify emerging risks at a global level and propose prevention strategies. AMR is one of the biggest threats to human health in the infectious disease environment. Whereas new genomic typing techniques such as whole genome sequencing (WGS) provide further insights into the mechanisms of spread of resistance, the role of the environment is not fully elucidated, nor is the role of plants as potential vehicles for spread of resistance. Historical trends and recent experience indicate that (re)-emergence and/or further spread of VBD within the EU is a matter of when rather than if. Standardised and validated vector monitoring programs are required to be implemented at an international level for continuous surveillance and assessment of potential threats. There are benefits to using WGS - such as a quicker and better response to outbreaks and additional evidence for source attribution. However, significant challenges need to be addressed, including method standardisation and validation to fully realise these benefits; barriers to data sharing; and establishing epidemiological capacity for cluster triage and response.

Scientific opinion on chronic wasting disease (II).

The European Commission asked EFSA for a scientific opinion on chronic wasting disease in two parts. Part one, on surveillance, animal health risk-based measures and public health risks, was published in January 2017. This opinion (part two) addresses the remaining Terms of Reference, namely, 'are the conclusions and recommendations in the EFSA opinion of June 2004 on diagnostic methods for chronic wasting disease still valid? If not, an update should be provided', and 'update the conclusions of the 2010 EFSA opinion on the results of the European Union survey on chronic wasting disease in cervids, as regards its occurrence in the cervid population in the European Union'. Data on the performance of authorised rapid tests in North America are not comprehensive, and are more limited than those available for the tests approved for statutory transmissible spongiform encephalopathies surveillance applications in cattle and sheep. There are no data directly comparing available rapid test performances in cervids. The experience in Norway shows that the Bio-Rad TeSeE™ SAP test, immunohistochemistry and western blotting have detected reindeer, moose and red deer cases. It was shown that testing both brainstem and lymphoid tissue from each animal increases the surveillance sensitivity. Shortcomings in the previous EU survey limited the reliability of inferences that could be made about the potential disease occurrence in Europe. Subsequently, testing activity in Europe was low, until the detection of the disease in Norway, triggering substantial testing efforts in that country. Available data neither support nor refute the conclusion that chronic wasting disease does not occur widely in the EU and do not preclude the possibility that the disease was present in Europe before the survey was conducted. It appears plausible that chronic wasting disease could have become established in Norway more than a decade ago.