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

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

Abstract 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...

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Main Authors: 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, Bethsabée Scheid, Miguel Ángel Miranda Chueca, Carlos Barceló, Javier Lucientes, Rosa Estrada, Alexander Mathis, Roger Venail, Wesley Tack, Rene Bødker
Format: Article
Language:English
Published: BMC 2020-04-01
Series:Parasites & Vectors
Subjects:
Culicoides abundance
Random Forest machine learning
Spatial predictions
Europe
Environmental variables
Culicoides seasonality
Online Access:http://link.springer.com/article/10.1186/s13071-020-04053-x

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http://link.springer.com/article/10.1186/s13071-020-04053-x

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