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Cette note présente une revue de littérature non exhaustive des données de piégeage de Culicoides en Europe afin de caractériser la diversité et les abondances des populations en zone de faune sauvage.

Background: Arthropod vectors such as ticks, mosqui- toes, sandflies and biting midges are of public and vet- erinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim: We aim to describe the methodology underlying VectorNet maps, encourage standardisation and eval- uate output. Methods: Vector distribution and surveillance activity data have been collected since 2010 from a combina- tion of literature searches, field-survey data by ento- mologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively vali- dated during data entry and mapping processes. Results: As of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at sub- national administrative unit resolution. On VectorNet maps, there are relatively few areas where surveil- lance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addi- tion, VectorNet maps show where species are absent. VectorNet's impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion: VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Depuis la réémergence du sérotype 8 de la fièvre catarrhale ovine (FCO) en France continentale en 2015, une surveillance entomologique des populations de Culicoides a été redéployée à l'échelle de la métropole entre novembre 2015 et avril 2018, complétant le réseau de piégeages déjà en place en Corse depuis 2002. Pour la saison hivernale 2017-2018, cette surveillance aura permis de déclarer 16 départements en zone saisonnièrement indemne sur des durées variables. Suite à l'arrêt de la surveillance en France continentale en avril 2018, le réseau a continué de fonctionner en Corse et au port de Sète. De plus, des missions ponctuelles de surveillance de l'espèce d'origine afrotropicale Culicoides imicola, vectrice majeure du virus de la FCO, ont eu lieu en alternance une année sur deux, dans les Pyrénées-Orientales, où l'espèce n'est plus capturée depuis 2012, et dans le Var et les Alpes-Maritimes où l'on observe une stabilité de la distribution géographique et des abondances des populations depuis l'installation de l'espèce détectée en 2003. Les données d'abondance et de distribution relevée sur le long terme dans cette zone suggèrent que cette espèce exotique pourrait avoir atteint sa limite géographique nord dans le bassin méditerranéen.

Comme suite à la réémergence du sérotype 8 de la fièvre catarrhale ovine (FCO)ovine en septembre 2015, un nouveau dispositif de surveillance entomologique des populations de Culicoides a été déployé en France continentale à l'automne-hiver 2016-2017, pour la deuxième année consécutive. Cette surveillance entomologique a permis de déterminer avec succès les périodes d'inactivité vectorielle relatives aux 24 zones de piégeage définies sur le territoire continental. Les informations issues de ce dispositif couplées à une surveillance de la circulation virale ont permis de déclarer jusqu'à seize départements de la zone réglementée en zones saisonnièrement indemnes (ZSI) sur des durées variables.

Additional file 1: Figure S1. Yearly variation of the mean abundance for each country. The abundance (y axis) was calculated as the mean all the observations (log transformed) from each country. Figure S2. QQ-plots of the residuals per month for the Obsoletus ensemble. Figure S3. QQ-plots of the residuals per month for the Pulicaris ensemble. Figure S4. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for the Obsoletus ensemble. a Maps from January to June. b maps from July to December. Figure S5. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for the Pulicaris ensemble. a Maps from January to June. b Maps from July to December. Figure S6. Comparison of the abundance maps for each month using Random Forest (RF) and Interpolations for Culicoides imicola. a Maps from January to June. b Maps from July to December. Figure S7. At a local scale, interpolation maps produce a smother surface between the farms compared to environmental driven RF, for which the predictions differ between adjacent pixels. The example shown in the figure corresponds to the August maps for the Obsoletus ensemble. Green dots: farms used for training, purple dots: farms within the test set.

Additional file 1: Table S1. List of specimens included in this study, along with their identification numbers (voucher code), countries and GenBank accession numbers for each DNA region.

Additional file 2: Table S1. Values (median and interquartile range) of the mean absolute error (MAE) and root mean square error (RMSE) for each vector zone.

Our understanding on the structure and role of viral communities in animal hosts has not yet reached the knowledge level attained on the bacteriome. This situation is, among others, probably due to technical constraints in adapting metagenomics, a main tool in bacteriome studies, to the characterisation of viral communities. Technical developments have been achieved for most steps of viral metagenomics. However, there is yet a key step that has received little attention, that of library preparation. This situation is surprising because developments in library preparation have largely facilitated bacteriome studies. Here, we present a library preparation optimized for metagenomics of RNA viruses from animals. The library has been designed to provide advantages found in metabarcoding libraries used in bacteriome studies, while allowing shotgun sequencing as required in viral metagenomics. We have validated a full metagenomics approach incorporating our library preparation and using mock viral communities. We have further tested our approach in two pilot studies with field-caught insects, all vectors of viral diseases. Our approach provided a fold increase in virus-like sequences compared to other studies, and nearly-full genomes from new virus species. Moreover, our results suggested conserved trends in virome composition in a mosquito species, and thus the existence of deterministic forces shaping its virome. Finally, the sensitivity of our approach was relatively good when compared to a commercial diagnostic PCR for the detection of an arbovirus in field-caught vectors. Our approach could facilitate studies on viral communities from animals and the democratisation of metagenomics in virus ecology.

Additional file 1: Table S1. Description of study sites and trap localization.

International audience

Vector abundance maps are a necessary step in mapping the risks associated with vector-borne diseases to help target surveillance and control actions. Risk mapping requires sampling vector species at different scales, which is made difficult by heterogeneity in vector spatial distribution and dynamics. In Morocco, Culicoides were responsible for African horse sickness (AHS) outbreaks in the 1960s and late 1980s. Since 2004, Morocco is facing an endemic situation of bluetongue virus (BTV) transmission. Our study aimed to produce first abundance maps for the most abundant Culicoides species, and risk maps for BTV and AHSV, across the country. We conducted a national cross-sectional survey using a stratified sampling strategy based on eco-agronomic zoning, for which we hypothesized the homogeneity of Culicoides diversity and dynamics. Historical collection time series were used to determine maximum abundance periods based on climate zonation. This strategy allowed to plan a national sampling of Culicoides abundance during a single collection season. Collections were conducted twice a year with 144 farms trapped. Culicoides were sampled for consecutive 48h using a suction light trap. We obtained a total of 262 samples under identification process. The results so far have shown that C. imicola was the most common species (present in at least 70% of the sites), followed by C. circumscriptus (absent at mild altitudes) and C. kingi (mostly present in the south). Culicoides obsoletus/C. scoticus have been collected frequently in the country, including in the south. This highlighted the wide and unexpected spatial distribution of these species from Scandinavia to North Africa reinforcing the existence of sibling species. Other species have also been identified, such as C. puncticollis, C. newsteadi, C. catanei/C. gegjelensis (rather present in the north on the coast), C. punctatus (rare in the south), C. pulicaris/C. lupicaris and C. kurensis. Interestingly, although C. paolae is mentioned in the literature as being associated with prickly pears in the Mediterranean basin, this species was absent in many areas heavily vegetated by this fig tree. This original dataset will be used to determine the ecological factors of the abundance and distribution of Culicoides of veterinary interest in order to provide accurate mapping of vector-related risks across Morocco.