TY - JOUR

T1 - Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

AU - Cuellar, Ana Carolina

AU - Jung Kjær, Lene

AU - Baum, Andreas

AU - Stockmarr, Anders

AU - Skovgard, Henrik

AU - Nielsen, Søren Achim

AU - Andersson, Mats Gunnar

AU - Lindström, Anders

AU - Chirico, Jan

AU - Lühken, Renke

AU - Steinke, Sonja

AU - Kiel, Ellen

AU - Gethmann, Jörn

AU - Conraths, Franz J

AU - Larska, Magdalena

AU - Smreczak, Marcin

AU - Orłowska, Anna

AU - Hamnes, Inger

AU - Sviland, Ståle

AU - Hopp, Petter

AU - Brugger, Katharina

AU - Rubel, Franz

AU - Balenghien, Thomas

AU - Garros, Claire

AU - Rakotoarivony, Ignace

AU - Allène, Xavier

AU - Lhoir, Jonathan

AU - Chavernac, David

AU - Delécolle, Jean-Claude

AU - Mathieu, Bruno

AU - Delécolle, Delphine

AU - Setier-Rio, Marie-Laure

AU - Venail, Roger

AU - Scheid, Bethsabée

AU - Chueca, Miguel Ángel Miranda

AU - Barceló, Carlos

AU - Lucientes, Javier

AU - Estrada, Rosa

AU - Mathis, Alexander

AU - Tack, Wesley

AU - Bødker, Rene

PY - 2018

Y1 - 2018

N2 - BackgroundBiting 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.MethodsWe 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.ResultsThe 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.ConclusionsThe 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.

AB - BackgroundBiting 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.MethodsWe 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.ResultsThe 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.ConclusionsThe 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.

U2 - 10.1186/s13071-018-3182-0

DO - 10.1186/s13071-018-3182-0

M3 - Journal article

C2 - 30497537

VL - 11

JO - Parasites & Vectors

JF - Parasites & Vectors

SN - 1756-3305

M1 - 608

ER -