Cristin-resultat-ID: 1771536
Sist endret: 31. januar 2020, 15:45
NVI-rapporteringsår: 2019
Resultat
Vitenskapelig artikkel
2019

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

Bidragsytere:
  • Lene Jung Kjær
  • Arnulf Soleng
  • Kristin Skarsfjord Edgar
  • Heidi Elisabeth Heggen Lindstedt
  • Katrine Mørk Paulsen
  • Åshild Kristine Andreassen
  • mfl.

Tidsskrift

Scientific Reports
ISSN 2045-2322
e-ISSN 2045-2322
NVI-nivå 1

Om resultatet

Vitenskapelig artikkel
Publiseringsår: 2019
Volum: 9
Hefte: 1
Artikkelnummer: 18144
Open Access

Importkilder

Scopus-ID: 2-s2.0-85075954448

Beskrivelse Beskrivelse

Tittel

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

Sammendrag

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, R2 from 0.52–0.58) whereas adult tick models performed poorly (normalized RMSE from 0.94–0.96, R2 from 0.04–0.10). Testing the models on 2017 data produced good results with normalized RMSE values from 0.59–1.13 and R2 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.

Bidragsytere

Lene Jung Kjær

  • Tilknyttet:
    Forfatter
    ved Danmarks Tekniske Universitet
  • Tilknyttet:
    Forfatter
    ved Københavns Universitet

Arnulf Soleng

  • Tilknyttet:
    Forfatter
    ved Avdeling for smittevern og beredskap ved Folkehelseinstituttet

Kristin Skarsfjord Edgar

  • Tilknyttet:
    Forfatter
    ved Avdeling for smittevern og beredskap ved Folkehelseinstituttet

Heidi Elisabeth Heggen Lindstedt

  • Tilknyttet:
    Forfatter
    ved Avdeling for smittevern og beredskap ved Folkehelseinstituttet

Katrine Mørk Paulsen

  • Tilknyttet:
    Forfatter
    ved Institutt for produksjonsdyrmedisin ved Norges miljø- og biovitenskapelige universitet
  • Tilknyttet:
    Forfatter
    ved Avdeling for virologi ved Folkehelseinstituttet
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