This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. AbstractGood knowledge on the disease situation and its impact on production is a base mechanism for designing health surveillance, risk analysis and biosecurity systems.Mediterranean marine fish farming, as any aquaculture production, is affected by various infectious diseases. However, seabass and seabream, the main produced species, are not listed as susceptible host species for the notifiable pathogens listed in the current EU legislation, which generates a lack of systematic reporting. The results presented in this study come from a survey directly to fish farms (50 hatchery and on-growing units from 10 Mediterranean countries), with data from 2015 to 2017, conducted by the H2020 project MedAID. Seabass showed a higher survival rate (85%) through a production cycle than seabream (80%) in spite of equal mortality due to pathogen infections (10%). The differences in survival may be explained by mortality 'of other causes'. Seabream and seabass have different disease profiles, and the profile is slightly different between geographical regions. Among the most important diseases, tenacibaculosis and vibriosis were identified in seabass and Sparicotyle chrysophrii (a gill fluke) and nodavirus in seabream. Correlating mortality data to management variables showed that increasing density, buying fingerlings from external sources and treatments due to disease are factors that negatively influence mortality rate. Most of the surveyed farms did not keep sufficient quality data to implement good health status reports and perform detailed impact studies, which shows the necessity of updating the current legislative framework to provide the basis for better reporting of relevant pathogens in the Mediterranean basin. K E Y W O R D Saquaculture, disease impact, disease situation, Mediterranean, seabass, seabream

The use of vaccines including aluminum (Al)-based adjuvants is widespread among small ruminants and other animals. They are associated with the appearance of transient injection site nodules corresponding to granulomas. This study aims to characterize the morphology of these granulomas, to understand the role of the Al adjuvant in their genesis, and to establish the presence of the metal in regional lymph nodes. A total of 84 male neutered lambs were selected and divided into 3 treatment groups of 28 animals each: (1) vaccine (containing Al-based adjuvant), (2) adjuvant-only, and (3) control. A total of 19 subcutaneous injections were performed in a time frame of 15 months. Granulomas and regional lymph nodes were evaluated by clinicopathological means. All of the vaccine and 92.3% of the adjuvant-only lambs presented injectionsite granulomas; the granulomas were more numerous in the group administered the vaccine. Bacterial culture in granulomas was always negative. Histologically, granulomas in the vaccine group presented a higher degree of severity. Al was specifically identified by lumogallion staining in granulomas and lymph nodes. Al median content was significantly higher (P < .001) in the lymph nodes of the vaccine group (82.65 mg/g) compared with both adjuvant-only (2.53 mg/g) and control groups (0.96 mg/g). Scanning transmission electron microscopy demonstrated aggregates of Al within macrophages in vaccine and adjuvant-only groups. In these two groups, Al-based adjuvants induce persistent, sterile, subcutaneous granulomas with macrophage-driven translocation of Al to regional lymph nodes. Local translocation of Al may induce further accumulation in distant tissues and be related to the appearance of systemic signs.

The high sensitivity of qPCR makes it a desirable diagnostic method in epidemiological surveillance programs. However, due to high costs, the use of pooling has been suggested. In this paper, an algorithm based on the Montecarlo method has been designed and implemented. The algorithm had been tested in many different situations, and finally it was validated with a real dataset. Moreover, based on the results obtained and depending on pooling conditions, a drastic decrease of sensitivity is observed.