Host-Seeking Activity of Bluetongue Virus Vectors: Endo/Exophagy and Circadian Rhythm of Culicoides in Western Europe

Feeding success of free-living hematophagous insects depends on their ability to be active when hosts are available and to reach places where hosts are accessible. When the hematophagous insect is a vector of pathogens, determining the components of host-seeking behavior is of primary interest for the assessment of transmission risk. Our aim was to describe endo/exophagy and circadian host-seeking activity of Palaearctic Culicoides species, which are major biting pests and arbovirus vectors, using drop traps and suction traps baited with four sheep, as bluetongue virus hosts. Collections were carried out in the field, a largely-open stable and an enclosed stable during six collection periods of 24 hours in April/May, in late June and in September/October 2010 in western France. A total of 986 Culicoides belonging to 13 species, mainly C. brunnicans and C. obsoletus, was collected on animal baits. Culicoides brunnicans was clearly exophagic, whereas C. obsoletus was able to enter stables. Culicoides brunnicans exhibited a bimodal pattern of host-seeking activity with peaks just after sunrise and sunset. Culicoides obsoletus was active before sunset in spring and autumn and after sunset in summer, thus illustrating influence of other parameters than light, especially temperature. Description of host-seeking behaviors allowed us to discuss control strategies for transmission of Culicoides-borne pathogens, such as bluetongue virus. However, practical vector-control recommendations are difficult to provide because of the variation in the degree of endophagy and time of host-seeking activity.This study was funded by CIRAD, by the Ministe`re de l’agriculture, de l’alimentation, de la peˆche, de la ruralite´ et de l’ame´nagement du terroire and by the EU FP7-HEALTH-2010-single-stage grant 261504 EDENext. This paper is catalogued by the EDENext Steering Committee as EDENext032 (http://www.edenext. eu). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study

How do species, population and active ingredient influence insecticide susceptibility in Culicoides biting midges (Diptera: Ceratopogonidae) of veterinary importance?

Background Culicoides biting midges are biological vectors of internationally important arboviruses of livestock and equines. Insecticides are often employed against Culicoides as a part of vector control measures, but systematic assessments of their efficacy have rarely been attempted. The objective of the present study is to determine baseline susceptibility of multiple Culicoides vector species and populations in Europe and Africa to the most commonly used insecticide active ingredients. Six active ingredients are tested: three that are based on synthetic pyrethroids (alpha-cypermethrin, deltamethrin and permethrin) and three on organophosphates (phoxim, diazinon and chlorpyrifos-methyl). Methods Susceptibility tests were conducted on 29,064 field-collected individuals of Culicoides obsoletus Meigen, Culicoides imicola Kieffer and a laboratory-reared Culicoides nubeculosus Meigen strain using a modified World Health Organization assay. Populations of Culicoides were tested from seven locations in four different countries (France, Spain, Senegal and South Africa) and at least four concentrations of laboratory grade active ingredients were assessed for each population. Results The study revealed that insecticide susceptibility varied at both a species and population level, but that broad conclusions could be drawn regarding the efficacy of active ingredients. Synthetic pyrethroid insecticides were found to inflict greater mortality than organophosphate active ingredients and the colony strain of C. nubeculosus was significantly more susceptible than field populations. Among the synthetic pyrethroids, deltamethrin was found to be the most toxic active ingredient for all species and populations. Conclusions The data presented represent the first parallel and systematic assessment of Culicoides insecticide susceptibility across several countries. As such, they are an important baseline reference to monitor the susceptibility status of Culicoides to current insecticides and also to assess the toxicity of new active ingredients with practical implications for vector control strategies. (Résumé d'auteur

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning

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

Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

Background: 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. Methods : 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. Results: 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. Conclusions: 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