Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance
Abstract 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 c...
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Language: | English |
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BMC
2018-11-01
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Series: | Parasites & Vectors |
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Online Access: | http://link.springer.com/article/10.1186/s13071-018-3182-0 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ana Carolina Cuéllar Lene Jung Kjær Andreas Baum Anders Stockmarr Henrik Skovgard Søren Achim Nielsen Mats Gunnar Andersson Anders Lindström Jan Chirico Renke Lühken Sonja Steinke Ellen Kiel Jörn Gethmann Franz J. Conraths Magdalena Larska Marcin Smreczak Anna Orłowska Inger Hamnes Ståle Sviland Petter Hopp Katharina Brugger Franz Rubel Thomas Balenghien Claire Garros Ignace Rakotoarivony Xavier Allène Jonathan Lhoir David Chavernac Jean-Claude Delécolle Bruno Mathieu Delphine Delécolle Marie-Laure Setier-Rio Roger Venail Bethsabée Scheid Miguel Ángel Miranda Chueca Carlos Barceló Javier Lucientes Rosa Estrada Alexander Mathis Wesley Tack René Bødker |
spellingShingle |
Ana Carolina Cuéllar Lene Jung Kjær Andreas Baum Anders Stockmarr Henrik Skovgard Søren Achim Nielsen Mats Gunnar Andersson Anders Lindström Jan Chirico Renke Lühken Sonja Steinke Ellen Kiel Jörn Gethmann Franz J. Conraths Magdalena Larska Marcin Smreczak Anna Orłowska Inger Hamnes Ståle Sviland Petter Hopp Katharina Brugger Franz Rubel Thomas Balenghien Claire Garros Ignace Rakotoarivony Xavier Allène Jonathan Lhoir David Chavernac Jean-Claude Delécolle Bruno Mathieu Delphine Delécolle Marie-Laure Setier-Rio Roger Venail Bethsabée Scheid Miguel Ángel Miranda Chueca Carlos Barceló Javier Lucientes Rosa Estrada Alexander Mathis Wesley Tack René Bødker Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance Parasites & Vectors Culicoides Random Forest Machine Learning Europe Monthly distribution Spatial distribution |
author_facet |
Ana Carolina Cuéllar Lene Jung Kjær Andreas Baum Anders Stockmarr Henrik Skovgard Søren Achim Nielsen Mats Gunnar Andersson Anders Lindström Jan Chirico Renke Lühken Sonja Steinke Ellen Kiel Jörn Gethmann Franz J. Conraths Magdalena Larska Marcin Smreczak Anna Orłowska Inger Hamnes Ståle Sviland Petter Hopp Katharina Brugger Franz Rubel Thomas Balenghien Claire Garros Ignace Rakotoarivony Xavier Allène Jonathan Lhoir David Chavernac Jean-Claude Delécolle Bruno Mathieu Delphine Delécolle Marie-Laure Setier-Rio Roger Venail Bethsabée Scheid Miguel Ángel Miranda Chueca Carlos Barceló Javier Lucientes Rosa Estrada Alexander Mathis Wesley Tack René Bødker |
author_sort |
Ana Carolina Cuéllar |
title |
Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance |
title_short |
Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance |
title_full |
Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance |
title_fullStr |
Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance |
title_full_unstemmed |
Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance |
title_sort |
monthly variation in the probability of presence of adult culicoides populations in nine european countries and the implications for targeted surveillance |
publisher |
BMC |
series |
Parasites & Vectors |
issn |
1756-3305 |
publishDate |
2018-11-01 |
description |
Abstract 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. |
topic |
Culicoides Random Forest Machine Learning Europe Monthly distribution Spatial distribution |
url |
http://link.springer.com/article/10.1186/s13071-018-3182-0 |
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doaj-85150d1098594c439ffa71d7c05875e12020-11-24T21:55:21ZengBMCParasites & Vectors1756-33052018-11-0111111910.1186/s13071-018-3182-0Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillanceAna Carolina Cuéllar0Lene Jung Kjær1Andreas Baum2Anders Stockmarr3Henrik Skovgard4Søren Achim Nielsen5Mats Gunnar Andersson6Anders Lindström7Jan Chirico8Renke Lühken9Sonja Steinke10Ellen Kiel11Jörn Gethmann12Franz J. Conraths13Magdalena Larska14Marcin Smreczak15Anna Orłowska16Inger Hamnes17Ståle Sviland18Petter Hopp19Katharina Brugger20Franz Rubel21Thomas Balenghien22Claire Garros23Ignace Rakotoarivony24Xavier Allène25Jonathan Lhoir26David Chavernac27Jean-Claude Delécolle28Bruno Mathieu29Delphine Delécolle30Marie-Laure Setier-Rio31Roger Venail32Bethsabée Scheid33Miguel Ángel Miranda Chueca34Carlos Barceló35Javier Lucientes36Rosa Estrada37Alexander Mathis38Wesley Tack39René Bødker40Division for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark (DTU)Division for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark (DTU)Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU)Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU)Department of Agroecology - Entomology and Plant Pathology, Aarhus UniversityDepartment of Science and Environment, Roskilde UniversityNational Veterinary Institute (SVA)National Veterinary Institute (SVA)National Veterinary Institute (SVA)Bernhard Nocht Institute for Tropical Medicine, WHO Collaborating Centre for Arbovirus and Hemorrhagic Fever Reference and Research National Reference Centre for Tropical Infectious DiseasesDepartment of Biology and Environmental Sciences, Carl von Ossietzky UniversityDepartment of Biology and Environmental Sciences, Carl von Ossietzky UniversityInstitute of Epidemiology, Friedrich Loeffler InstituteInstitute of Epidemiology, Friedrich Loeffler InstituteDepartment of Virology, National Veterinary Research InstituteDepartment of Virology, National Veterinary Research InstituteDepartment of Virology, National Veterinary Research InstituteNorwegian Veterinary InstituteNorwegian Veterinary InstituteNorwegian Veterinary InstituteInstitute for Veterinary Public HealthInstitute for Veterinary Public HealthCIRAD, UMR ASTRECIRAD, UMR ASTRECIRAD, UMR ASTRECIRAD, UMR ASTRECIRAD, UMR ASTRECIRAD, UMR ASTREInstitute of Parasitology and Tropical Pathology of Strasbourg, EA7292, Université de StrasbourgInstitute of Parasitology and Tropical Pathology of Strasbourg, EA7292, Université de StrasbourgInstitute of Parasitology and Tropical Pathology of Strasbourg, EA7292, Université de StrasbourgEID MéditerranéeEID MéditerranéeEID MéditerranéeLaboratory of Zoology, University of the Balearic IslandsLaboratory of Zoology, University of the Balearic IslandsDepartment of Animal Pathology, University of ZaragozaDepartment of Animal Pathology, University of ZaragozaInstitute of Parasitology, University of ZürichAvia-GIS NVDivision for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark (DTU)Abstract 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.http://link.springer.com/article/10.1186/s13071-018-3182-0CulicoidesRandom ForestMachine LearningEuropeMonthly distributionSpatial distribution |