The European Commission has requested EFSA to assess animal diseases according to the criteria as laid down in Articles 5, 7, 8 and Annex IV for the purpose of categorisation of diseases in accordance with Article 9 of the Regulation (EU) No 2016/429 (Animal Health Law). This scientific opinion addresses the ad hoc method developed for assessing any animal disease for the listing and categorisation of diseases within the Animal Health Law (AHL) framework. The assessment of individual diseases is addressed in distinct scientific opinions that are published separately. The assessment of Articles 5, 8 and 9 criteria is performed on the basis of the information collected according to Article 7 criteria. For that purpose, Article 7 criteria were structured into parameters and the information was collected at parameter level. The resulting fact sheets on the profile and impact of each disease were compiled by disease scientists. A mapping was developed to identify which parameters from Article 7 were needed to inform each Article 5, 8 and 9 criterion. Specifically, for Articles 5 and 9 criteria, a categorical assessment was performed, by applying an expert judgement procedure, based on the mapped information. The judgement was performed by EFSA Panel experts on Animal Health and Welfare in two rounds, individual and collective judgement. The output of the expert judgement on the criteria of Articles 5 and 9 for each disease is composed by the categorical answer, and for the questions where no consensus was reached, the different supporting views are reported.

Data obtained by a Spanish national surveillance programme in 2005 were used to develop climatic models for predictions of the distribution of the bluetongue virus (BTV) vectors Culicoides imicola Kieffer (Diptera: Ceratopogonidae) and the Culicoides obsoletus group Meigen throughout the Iberian peninsula. Models were generated using logistic regression to predict the probability of species occurrence at an 8-km spatial resolution. Predictor variables included the annual mean values and seasonalities of a remotely sensed normalized difference vegetation index (NDVI), a sun index, interpolated precipitation and temperature. Using an information-theoretic paradigm based on Akaike's criterion, a set of best models accounting for 95% of model selection certainty were selected and used to generate an average predictive model for each vector. The predictive performances (i.e. the discrimination capacity and calibration) of the average models were evaluated by both internal and external validation. External validation was achieved by comparing average model predictions with surveillance programme data obtained in 2004 and 2006. The discriminatory capacity of both models was found to be reasonably high. The estimated areas under the receiver operating characteristic (ROC) curve (AUC) were 0.78 and 0.70 for the C. imicola and C. obsoletus group models, respectively, in external validation, and 0.81 and 0.75, respectively, in internal validation. The predictions of both models were in close agreement with the observed distribution patterns of both vectors. Both models, however, showed a systematic bias in their predicted probability of occurrence: observed occurrence was systematically overestimated for C. imicola and underestimated for the C. obsoletus group. Average models were used to determine the areas of spatial coincidence of the two vectors. Although their spatial distributions were highly complementary, areas of spatial coincidence were identified, mainly in Portugal and in the southwest of peninsular Spain. In a hypothetical scenario in which both Culicoides members had similar vectorial capacity for a BTV strain, these areas should be considered of special epidemiological concern because any epizootic event could be intensified by consecutive vector activity developed for both species during the year; consequently, the probability of BTV spreading to remaining areas occupied by both vectors might also be higher.

Bluetongue (BT) is still present in Europe and the introduction of new serotypes from endemic areas in the African continent is a possible threat. Culicoides imicola remains one of the most relevant BT vectors in Spain and research on the environmental determinants driving its life cycle is key to preventing and controlling BT. Our aim was to improve our understanding of the biotic and abiotic determinants of C. imicola by modelling its present abundance, studying the spatial pattern of predicted abundance in relation to BT outbreaks, and investigating how the predicted current distribution and abundance patterns might change under future (2011–2040) scenarios of climate change according to the Intergovernmental Panel on Climate Change. C. imicola abundance data from the bluetongue national surveillance programme were modelled with spatial, topoclimatic, host and soil factors. The influence of these factors was further assessed by variation partitioning procedures. The predicted abundance of C. imicola was also projected to a future period. Variation partitioning demonstrated that the pure effect of host and topoclimate factors explained a high percentage (>80%) of the variation. The pure effect of soil followed in importance in explaining the abundance of C. imicola. A close link was confirmed between C. imicola abundance and BT outbreaks. To the best of our knowledge, this study is the first to consider wild and domestic hosts in predictive modelling for an arthropod vector. The main findings regarding the near future show that there is no evidence to suggest that there will be an important increase in the distribution range of C. imicola; this contrasts with an expected increase in abundance in the areas where it is already present in mainland Spain. What may be expected regarding the future scenario for orbiviruses in mainland Spain, is that higher predicted C. imicola abundance may significantly change the rate of transmission of orbiviruses.