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

Show simple item record

dc.contributor.author Cuéllar, Ana Carolina
dc.contributor.author Jung Kjær, Lene
dc.contributor.author Baum, Andreas
dc.contributor.author Stockmarr, Anders
dc.contributor.author Skovgard, Henrik
dc.contributor.author Achim Nielsen, Søren
dc.contributor.author Gunnar Andersson, Mats
dc.contributor.author Lindström, Anders
dc.contributor.author Chirico, Jan
dc.contributor.author Lühken, Renke
dc.contributor.author Steinke, Sonja
dc.contributor.author Kiel, Ellen
dc.contributor.author Gethmann, Jörn
dc.contributor.author Conraths, Franz J.
dc.contributor.author Larska, Magdalena
dc.contributor.author Smreczak, Marcin
dc.contributor.author Orłowska, Anna
dc.contributor.author Venail, Roger
dc.contributor.author Hamnes, Inger
dc.contributor.author Sviland, Ståle
dc.contributor.author Hopp, Petter
dc.contributor.author Brugger, Katharina
dc.contributor.author Rubel, Franz
dc.contributor.author Balenghien, Thomas
dc.contributor.author Garros, Claire
dc.contributor.author Rakotoarivony, Ignace
dc.contributor.author Allène, Xavier
dc.contributor.author Lhoir, Jonathan
dc.contributor.author Chavernac, David
dc.contributor.author Delécolle, Jean-Claude
dc.contributor.author Mathieu, Bruno
dc.contributor.author Delécolle, Delphine
dc.contributor.author Setier-Rio, Marie-Laure
dc.contributor.author Scheid, Bethsabée
dc.contributor.author Miranda Chueca, Miguel Ángel
dc.contributor.author Barceló, Carlos
dc.contributor.author Lucientes, Javier
dc.contributor.author Estrada, Rosa
dc.contributor.author Mathis, Alexander
dc.date.accessioned 2020-04-20T07:11:50Z
dc.date.available 2020-04-20T07:11:50Z
dc.identifier.uri http://hdl.handle.net/11201/152034
dc.description.abstract [eng] 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 diferences in abundance between countries but was not able to predict vector abundance at individual farm level.
dc.format application/pdf
dc.relation.isformatof https://doi.org/10.1186/s13071-020-04053-x
dc.relation.ispartof Parasites & Vectors, 2020, vol. 13, num. 194, p. 1-18
dc.rights , 2020
dc.subject.classification 57 - Biologia
dc.subject.other 57 - Biological sciences in general
dc.title Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning
dc.type info:eu-repo/semantics/article
dc.date.updated 2020-04-20T07:11:51Z
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.identifier.doi https://doi.org/10.1186/s13071-020-04053-x


Files in this item

This item appears in the following Collection(s)

Show simple item record