Background: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for farmers in Europe. Vector abundance is a key factor in determining the risk of vector-borne disease spread and it is, therefore, important to predict the abundance of Culicoides species involved in the transmission of these pathogens. The objectives of this study were to model and map the monthly abundances of Culicoides in Europe. Methods: We obtained entomological data from 904 farms in nine European countries (Spain, France, Germany, Switzerland, Austria, Poland, Denmark, Sweden and Norway) from 2007 to 2013. Using environmental and climatic predictors from satellite imagery and the machine learning technique Random Forests, we predicted the monthly average abundance at a 1 km² resolution. We used independent test sets for validation and to assess model performance. Results: The predictive power of the resulting models varied according to month and the Culicoides species/ensembles predicted. Model performance was lower for winter months. Performance was higher for the Obsoletus ensemble, followed by the Pulicaris ensemble, while the model for Culicoides imicola showed a poor performance. Distribution and abundance patterns corresponded well with the known distributions in Europe. The Random Forests model approach was able to distinguish differences in abundance between countries but was not able to predict vector abundance at individual farm level. Conclusions: The models and maps presented here represent an initial attempt to capture large scale geographical and temporal variations in Culicoides abundance. The models are a first step towards producing abundance inputs for R₀ modelling of Culicoides-borne infections at a continental scale.

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain.

Astroviruses (AstVs) are small RNA viruses characterized by a high mutation rate, the ability to recombine, and interspecies transmission, which allows them to infect a multitude of hosts including humans, companion animals, and farmed animals as well as wildlife. AstVs are stable in the environment, and their transmission is usually through the fecal–oral route or via contaminated water and food. Although direct zoonotic transmission was not confirmed, interspecies transmission events have occurred or have been indicated to occur in the past between wild and domestic animals and humans. They cause large economic losses, mainly in the poultry sector, due to gastroenteritis and mortality. In young children, they are the second most common cause of diarrhea. This study involved 166 intestine samples and pools of spleen, lymph node, and kidney samples collected from 352 wild animals, 52 pigs, and 31 companion animals. Astroviruses were detected in the intestine samples and were separately detected in pools of tissue samples prepared for individual animals using a heminested RT-PCR protocol. Amplicons were subjected to Sanger sequencing, and a phylogenetic analysis of 320 nt RNA-dependent RNA polymerase (RdRp) fragments referring to known nt sequences of astroviruses was performed. Astroviral RNA was detected in the intestine samples and/or tissue pools of red foxes (nine positive intestines and six positive tissue pools), rats (two positive intestines and three positive tissue pools), a cat (one AstV detected in an intestine sample), pigs (eight positive tissue pools), and wild boars (two positive pools of spleens, kidneys, and lymph nodes). No astroviral RNA was detected in wild mustelids, dogs, or other small wild animals including rodents. A phylogenetic analysis revealed that the astroviruses detected during this study were mostly host-specific, such as porcine, canine, and rat astroviruses that were highly homologous to the sequences of reference strains. In one of two wild boars, an AstV distinct to porcine species was found with the highest nt identity to Avastroviruses, i.e., turkey astroviruses, which suggests potential cross-species transmission of the virus, as previously described. Here, we present the first detection of astroviruses in the population of wild animals, companion animals, and pigs in Poland, confirming that astroviruses are frequent pathogens circulating in animals in the field. Our study also suggests potential cross-species transmission of Avaastrovirus to wild boars; however, further molecular characterization is needed.