Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe

  • Els Ducheyne Avia-GIS, Zoersel, Belgium.
  • Johannes Charlier Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
  • Jozef Vercruysse Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Ghent, Belgium.
  • Laura Rinaldi Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy.
  • Annibale Biggeri Department of Statistics, Informatics and Applications, University of Florence, Florence, Italy.
  • Janina Demeler Institute for Parasitology and Tropical Veterinary Medicine, Freie Universität Berlin, Berlin, Germany.
  • Christina Brandt Institute for Parasitology and Tropical Veterinary Medicine, Freie Universität Berlin, Berlin, Germany.
  • Theo de Waal UCD School of Veterinary Medicine, University College Dublin, Dublin, Ireland.
  • Nikolaos Selemetas UCD School of Veterinary Medicine, University College Dublin, Dublin, Ireland.
  • Johan Höglund Department of Biomedical Sciences and Veterinary Public Health, Section for Parasitology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
  • Jaroslaw Kaba Department of Large Animal Diseases, Faculty of Veterinary Medicine, Warsaw University of Life Sciences, Warsaw, Poland.
  • Slawomir J. Kowalczyk Department of Large Animal Diseases, Faculty of Veterinary Medicine, Warsaw University of Life Sciences, Warsaw, Poland.
  • Guy Hendrickx | ghendrickx@avia-gis.com Avia-GIS, Zoersel, Belgium.

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.

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Published
2015-03-19
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Original Articles
Keywords:
fasciolosis, dairy cattle, animal health, spatial modelling, Europe
Statistics
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How to Cite
Ducheyne, E., Charlier, J., Vercruysse, J., Rinaldi, L., Biggeri, A., Demeler, J., Brandt, C., de Waal, T., Selemetas, N., Höglund, J., Kaba, J., Kowalczyk, S. J., & Hendrickx, G. (2015). Modelling the spatial distribution of Fasciola hepatica in dairy cattle in Europe. Geospatial Health, 9(2), 261-270. https://doi.org/10.4081/gh.2015.348

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