Predicting the spatial abundance of Ixodes ricinus ticks in southern Scandinavia using environmental and climatic data.

Autor: Jung Kjær L; Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark. lenju@sund.ku.dk.; Department for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark, Lyngby, Denmark. lenju@sund.ku.dk., Soleng A; Department of Pest Control, Norwegian Institute of Public Health, Oslo, Norway., Edgar KS; Department of Pest Control, Norwegian Institute of Public Health, Oslo, Norway., Lindstedt HEH; Department of Pest Control, Norwegian Institute of Public Health, Oslo, Norway., Paulsen KM; Department of Virology, Norwegian Institute of Public Health, Oslo, Norway.; Department of Production Animal Clinical Sciences, Norwegian University of Life Sciences, Oslo, Norway., Andreassen ÅK; Department of Virology, Norwegian Institute of Public Health, Oslo, Norway., Korslund L; Department of Natural Sciences, University of Agder, Kristiansand, Norway., Kjelland V; Department of Natural Sciences, University of Agder, Kristiansand, Norway.; Sørlandet Hospital Health Enterprise, Research Unit, Kristiansand, Norway., Slettan A; Department of Natural Sciences, University of Agder, Kristiansand, Norway., Stuen S; Department of Production Animal Clinical Sciences, Section of Small Ruminant Research, Norwegian University of Life Sciences, Sandnes, Norway., Kjellander P; Department of Ecology, Wildlife Ecology Unit, Swedish University of Agricultural Sciences, Grimsö, Sweden., Christensson M; Department of Ecology, Wildlife Ecology Unit, Swedish University of Agricultural Sciences, Grimsö, Sweden., Teräväinen M; Department of Ecology, Wildlife Ecology Unit, Swedish University of Agricultural Sciences, Grimsö, Sweden., Baum A; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark., Klitgaard K; Department for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark, Lyngby, Denmark., Bødker R; Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark.; Department for Diagnostics and Scientific Advice, National Veterinary Institute, Technical University of Denmark, Lyngby, Denmark.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2019 Dec 02; Vol. 9 (1), pp. 18144. Date of Electronic Publication: 2019 Dec 02.
DOI: 10.1038/s41598-019-54496-1
Abstrakt: Recently, focus on tick-borne diseases has increased as ticks and their pathogens have become widespread and represent a health problem in Europe. Understanding the epidemiology of tick-borne infections requires the ability to predict and map tick abundance. We measured Ixodes ricinus abundance at 159 sites in southern Scandinavia from August-September, 2016. We used field data and environmental variables to develop predictive abundance models using machine learning algorithms, and also tested these models on 2017 data. Larva and nymph abundance models had relatively high predictive power (normalized RMSE from 0.65-0.69, R 2 from 0.52-0.58) whereas adult tick models performed poorly (normalized RMSE from 0.94-0.96, R 2 from 0.04-0.10). Testing the models on 2017 data produced good results with normalized RMSE values from 0.59-1.13 and R 2 from 0.18-0.69. The resulting 2016 maps corresponded well with known tick abundance and distribution in Scandinavia. The models were highly influenced by temperature and vegetation, indicating that climate may be an important driver of I. ricinus distribution and abundance in Scandinavia. Despite varying results, the models predicted abundance in 2017 with high accuracy. The models are a first step towards environmentally driven tick abundance models that can assist in determining risk areas and interpreting human incidence data.
Databáze: MEDLINE
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