Fish and other seafood are important sources of nutrients, but they are also sources of chemical contaminants that may cause adverse health effects. This article aimed to identify existing risk–benefit assessments (RBA) of fish, shellfish, and other seafood, compare methodologies, discuss differences and commonalities in findings, and identify limitations and ways forward for future studies. We conducted a scoping review of the scientific literature of studies in all languages published from 2000 through April 2019. We identified 106 RBA of fish and other seafood across Europe, Asia, North America, Africa, and at the global level. Studies were heterogeneous in terms of types of fish and other seafood considered, beneficial and adverse compounds assessed, and overall methodology. Collected data showed that a diet consisting of a variety of lean and fatty fish and other seafood is recommended for the overall population and that women of childbearing age and children should limit the consumption of fish and other seafood types that have a high likelihood of contamination. Our review emphasizes the need for evidence-based, up-to-date, and harmonized approaches in RBA in general.

The new European regulation on minimum quality requirements (MQR) for water reuse (EU, 2020/741) was launched in May 2020 and describes the directives for the use of reclaimed water for agricultural irrigation. This Regulation will be directly applicable in all Member States from 26 June 2023. Since its publication in 2020, concerns have raised about potential non-compliance situations in water reuse systems. The present study represents a case study where three different water reuse systems have been monitored to establish their compliance with the MQR. Each water reuse system includes a wastewater treatment plant (WWTP), a distribution/storage system and an end-user point, where water is used for irrigation of leafy greens. The selected water reuse systems allowed us to compare the efficacy of water treatments implemented in two WWTPs as well as the impact of three different irrigation systems (drip, furrow and overhead irrigation). The presence and concentration of indicator microorganisms (Escherichia coli and C. perfringens spores) as well as pathogenic bacteria (Shiga toxin-producing, E. coli (STEC), E. coli O157:H7, and Salmonella spp.) were monitored in different sampling points (influent and effluent of the WWTPs, water reservoirs located at the distribution system and the end-user point at the irrigation system as well as in the leafy greens during their growing cycle. Average levels of E. coli (0.73 ± 1.20 log cfu E. coli/100 mL) obtained at the point where the WWTP operator delivers reclaimed water to the next actor in the chain, defined in the European regulation as the 'point of compliance', were within the established MQR (<1 log cfu/100 mL) (EU, 2020/741). On the other hand, average levels of E. coli at the end-user point (1.0 ± 1.2 log cfu/100 mL) were below the recommended threshold (2 log cfu E. coli/100 mL) for irrigation water based on the guidance document on microbiological risks in fresh fruits and vegetables at primary production (EC, 2017/C_163/01). However, several outlier points were observed among the samples taken at the irrigation point, which were linked to a specific cross-contamination event within the distribution/storage system. Regarding pathogenic bacteria, water samples from the influent of the WWTPs showed a 100% prevalence, while only 5% of the effluent samples were positive for any of the monitored pathogenic bacteria. Obtained results indicate that reclaimed water produced in the selected water reuse system is suitable to be used as irrigation water. However, efforts are necessary not only in the establishment of advance disinfection treatments but also in the maintenance of the distribution/storage systems.

Variability is inherent in biology and also substantial for microbial populations. In the context of food safety risk assessment, it refers to differences in the response of different bacterial strains (between-strain variability) and different cells (within-strain variability) to the same condition (e.g. inactivation treatment). However, its quantification based on empirical observations and its incorporation in predictive models is a challenge for both experimental design and (statistical) analysis. In this article we propose the use of multilevel models to quantify (different levels of) variability and uncertainty and include them in the predictions. As proof of concept, we analyse the microbial inactivation of Listeria monocytogenes to thermal treatments including different levels of variability (between-strain and within-strain) and uncertainty. The relationship between the microbial count and time was expressed using a (non-linear) Weibullian model. Moreover, we defined stochastic hypotheses to describe the different types of variation at the level of the kinetic parameters, as well as in the observations (microbial counts). The model parameters (kinetic parameters and variances) are estimated using Bayesian statistics. The multilevel approach was compared against an analogous, single-level model. The multilevel methodology shrinks extreme parameter estimates towards the mean according to uncertainty, thus mitigating overfitting. In addition, this approach enables to easily incorporate different levels of variation (between-strain and/or within-strain variability and/or uncertainty) in the predictions. On the other hand, multilevel (Bayesian) models are more complex to define, implement, analyse and communicate than single-level models. Nevertheless, their ability to incorporate different sources of variability in predictions make them very suitable for Quantitative Microbial Risk Assessment.