title: Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe.
abstract: A harmonized sampling approach in combination with spatial modelling is required to update current knowledge of fasciolosis in dairy cattle in Europe. Within the scope of the EU project GLOWORM, samples from 3,359 randomly selected farms in 849 municipalities in Belgium, Germany, Ireland, Poland and Sweden were collected and their infection status assessed using an indirect bulk tank milk (BTM) enzyme-linked immunosorbent assay (ELISA). Dairy farms were considered exposed when the optical density ratio (ODR) exceeded the 0.3 cut-off. Two ensemble-modelling techniques, Random Forests (RF) and Boosted Regression Trees (BRT), were used to obtain the spatial distribution of the probability of exposure to Fasciola hepatica using remotely sensed environmental variables (1-km spatial resolution) and interpolated values from meteorological stations as predictors. The median ODRs amounted to 0.31, 0.12, 0.54, 0.25 and 0.44 for Belgium, Germany, Ireland, Poland and southern Sweden, respectively. Using the 0.3 threshold, 571 municipalities were categorized as positive and 429 as negative. RF was seen as capable of predicting the spatial distribution of exposure with an area under the receiver operation characteristic (ROC) curve (AUC) of 0.83 (0.96 for BRT). Both models identified rainfall and temperature as the most important factors for probability of exposure. Areas of high and low exposure were identified by both models, with BRT better at discriminating between low-probability and high-probability exposure; this model may therefore be more useful in practise. Given a harmonized sampling strategy, it should be possible to generate robust spatial models for fasciolosis in dairy cattle in Europe to be used as input for temporal models and for the detection of deviations in baseline probability. Further research is required for model output in areas outside the eco-climatic range investigated.
authors.affiliation: Avia-GIS, Zoersel. ghendrickx@avia-gis.com.
authors.forename: Els
authors.initials: E
authors.lastname: Ducheyne
authors.forename: Johannes
authors.initials: J
authors.lastname: Charlier
authors.forename: Jozef
authors.initials: J
authors.lastname: Vercruysse
authors.forename: Laura
authors.initials: L
authors.lastname: Rinaldi
authors.forename: Annibale
authors.initials: A
authors.lastname: Biggeri
authors.forename: Janina
authors.initials: J
authors.lastname: Demeler
authors.forename: Christina
authors.initials: C
authors.lastname: Brandt
authors.forename: Theo
authors.initials: T
authors.lastname: De Waal
authors.forename: Nikolaos
authors.initials: N
authors.lastname: Selemetas
authors.forename: Johan
authors.initials: J
authors.lastname: Höglund
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Kaba
authors.forename: Slawomir J
authors.initials: SJ
authors.lastname: Kowalczyk
authors.forename: Guy
authors.initials: G
authors.lastname: Hendrickx
mesh_terms: D000818:Animals; D002417:Cattle; D002418:Cattle Diseases; D003430:Cross-Sectional Studies; D003612:Dairying; D004797:Enzyme-Linked Immunosorbent Assay; D005060:Europe / Q000453:epidemiology; D005211:Fascioliasis / Q000662:veterinary*; D005260:Female; D008892:Milk / Q000469:parasitology; D015233:Models, Statistical; D012372:ROC Curve; D011891:Rain; D062206:Spatial Analysis; D013696:Temperature