Increasing world population worsens the serious problem of food security in developing countries. On the other hand in industrialized countries, where the problem of food security is of minor concern, health problems related to food refer to 2 main factors: food safety and environmental sustainability of food production. For these reasons, new ways must be found to increase yields while preserving food quality, natural habitats, and biodiversity. Insects could be of great interest as a possible solution due to their capability to satisfy 2 different requirements: (i) they are an important source of protein and other nutrients; (ii) their use as food has ecological advantages over conventional meat and, in the long run, economic benefits. However, little is known on the food safety side and this can be of critical importance to meet society's approval, especially if people are not accustomed to eating insects. This paper aims to collect information in order to evaluate how insects could be safely used as food and to discuss nutritional data to justify why insect food sources can no longer be neglected. Legislative issues will also be discussed.

The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractUncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. It is therefore relevant in all EFSA's scientific assessments and also necessary, to ensure that the assessment conclusions provide reliable information for decisionmaking. The form and extent of uncertainty analysis, and how the conclusions should be reported, vary widely depending on the nature and context of each assessment and the degree of uncertainty that is present. This document provides concise guidance on how to identify which options for uncertainty analysis are appropriate in each assessment, and how to apply them. It is accompanied by a separate, supporting opinion that explains the key concepts and principles behind this Guidance, and describes the methods in more detail.

EFSA requested the Scientific Committee to develop a guidance document on the use of the weight of evidence approach in scientific assessments for use in all areas under EFSA's remit. The guidance document addresses the use of weight of evidence approaches in scientific assessments using both qualitative and quantitative approaches. Several case studies covering the various areas under EFSA's remit are annexed to the guidance document to illustrate the applicability of the proposed approach. Weight of evidence assessment is defined in this guidance as a process in which evidence is integrated to determine the relative support for possible answers to a question. This document considers the weight of evidence assessment as comprising three basic steps: (1) assembling the evidence into lines of evidence of similar type, (2) weighing the evidence, (3) integrating the evidence. The present document identifies reliability, relevance and consistency as three basic considerations for weighing evidence.

The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

The pMLST method was suitable for rapid and easy subtyping of IncI1 plasmids. This study demonstrates that the pMLST method can contribute to the epidemiological description of circulation of specific resistance plasmids among beta-lactamase producers isolated from animals and humans.

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][2010][2011][2012][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. Acknowledgements: The Panel wishes to thank the hearing experts: Andrew Hart and Sophie Roussel for the support provided to this scientific output. The Panel also wishes to thank the consortia of the three outsourcing activities under 'Closing gaps for performing a risk assessment on L. monocytogenes in RTE foods' for their collaboration. In addition, R egis Pouillot is thanked for sharing the dose response model as described in Pouillot et al. (2015). Also the epidemiologists and microbiologists of the nominated public health contact points for listeriosis and Listeria isolates in the European Food-and Waterborne Diseases and Zoonoses network (FWD-Net) are thanked for replying to the questionnaire related to the surveillance of listeriosis.

EFSA is requested to assess the safety of a broad range of biological agents in the context of notification for market authorisation as sources of food and feed additives, food enzymes and plant protection products. The qualified presumption of safety (QPS) assessment was developed to provide a harmonised generic preassessment to support safety risk assessments performed by EFSA's scientific Panels. The safety of unambiguously defined biological agents (at the highest taxonomic unit appropriate for the purpose for which an application is intended), and the completeness of the body of knowledge are assessed. Identified safety concerns for a taxonomic unit are, where possible and reasonable in number, reflected as 'qualifications' in connection with a recommendation for a QPS status. The list of QPS recommended biological agents was reviewed and updated in the current opinion and therefore becomes the valid list. The 2016 update reviews previously assessed microorganisms including bacteria, yeasts and viruses used for plant protection purposes following an Extensive Literature Search strategy. The taxonomic units related to the new notifications received since the 2013 QPS opinion, were periodically evaluated for a QPS status and the results published as Statements of the BIOHAZ Panel. Carnobacterium divergens, Lactobacillus diolivorans, Microbacterium imperiale, Pasteuria nishizawae, Pediococcus parvulus, Bacillus flexus, Bacillus smithii, Xanthomonas campestris and Candida cylindracea were recommended for the QPS list. All taxonomic units previously recommended for the 2013 QPS list had their status reconfirmed as well their qualifications with the exception of Pasteuria nishizawae for which the qualification was removed. The exclusion of filamentous fungi and enterococci from the QPS evaluations was reconsidered but monitoring will be maintained and the status will be re-evaluated in the next QPS Opinion update. Evaluation of bacteriophages should remain as a case-by-case procedure and should not be considered for QPS status. Acknowledgements: The BIOHAZ Panel wishes to thank the EFSA staff member: Mirena Ivanova for the support provided to this scientific output.

To meet the general requirement for transparency in EFSA's work, all its scientific assessments must consider uncertainty. Assessments must say clearly and unambiguously what sources of uncertainty have been identified and what is their impact on the assessment conclusion. This applies to all EFSA's areas, all types of scientific assessment and all types of uncertainty affecting assessment. This current Opinion describes the principles and methods supporting a concise Guidance Document on Uncertainty in EFSA's Scientific Assessment, published separately. These documents do not prescribe specific methods for uncertainty analysis but rather provide a flexible framework within which different methods may be selected, according to the needs of each assessment. Assessors should systematically identify sources of uncertainty, checking each part of their assessment to minimise the risk of overlooking important uncertainties. Uncertainty may be expressed qualitatively or quantitatively. It is neither necessary nor possible to quantify separately every source of uncertainty affecting an assessment. However, assessors should express in quantitative terms the combined effect of as many as possible of identified sources of uncertainty. The guidance describes practical approaches. Uncertainty analysis should be conducted in a flexible, iterative manner, starting at a level appropriate to the assessment and refining the analysis as far as is needed or possible within the time available. The methods and results of the uncertainty analysis should be reported fully and transparently. Every EFSA Panel and Unit applied the draft Guidance to at least one assessment in their work area during a trial period of one year. Experience gained in this period resulted in improved guidance. The Scientific Committee considers that uncertainty analysis will be unconditional for EFSA Panels and staff and must be embedded into scientific assessment in all areas of EFSA's work.