Abstract
BackgroundTick-borne diseases have become increasingly common in recent decades and present a health problem in many parts of Europe. Control and prevention of these diseases require a better understanding of vector distribution.AimOur aim was to create a model able to predict the distribution of Ixodes ricinus nymphs in southern Scandinavia and to assess how this relates to risk of human exposure.MethodsWe measured the presence of I. ricinus tick nymphs at 159 stratified random lowland forest and meadow sites in Denmark, Norway and Sweden by dragging 400 m transects from August to September 2016, representing a total distance of 63.6 km. Using climate and remote sensing environmental data and boosted regression tree modelling, we predicted the overall spatial distribution of I. ricinus nymphs in Scandinavia. To assess the potential public health impact, we combined the predicted tick distribution with human density maps to determine the proportion of people at risk.ResultsOur model predicted the spatial distribution of I. ricinus nymphs with a sensitivity of 91% and a specificity of 60%. Temperature was one of the main drivers in the model followed by vegetation cover. Nymphs were restricted to only 17.5% of the modelled area but, respectively, 73.5%, 67.1% and 78.8% of the human populations lived within 5 km of these areas in Denmark, Norway and Sweden.ConclusionThe model suggests that increasing temperatures in the future may expand tick distribution geographically in northern Europe, but this may only affect a small additional proportion of the human population.
Highlights
Ticks are one of the most important vectors for pathogens, impacting a wide range of vertebrates, and transmit more pathogens than any other arthropod [1,2]
Assuming that tick presence in the areas of northern Norway and Sweden not included in the modelled region was below 50% probability of presence (PP), the percentage of a predicted tick risk of at least 50% was 5.1% and 20.5% of the total land area of Norway and Sweden, respectively
Using the machine learning technique Boosted Regression Trees, we were able to create maps of the probability of nymphal I. ricinus presence in Scandinavia with high predictive power based on a standardised repeatable procedure
Summary
Ticks are one of the most important vectors for pathogens, impacting a wide range of vertebrates, and transmit more pathogens than any other arthropod [1,2]. In Europe, the main vector for tick-borne pathogens is Ixodes ricinus [3,4], which is the most common tick species in Scandinavia [3,4,5]. The incidence and geographical range of tick-borne diseases have increased [3,6,7] and pose a risk to both human and animal health. Aim: Our aim was to create a model able to predict the distribution of Ixodes ricinus nymphs in southern Scandinavia and to assess how this relates to risk of human exposure. Conclusion: The model suggests that increasing temperatures in the future may expand tick distribution geographically in northern Europe, but this may only affect a small additional proportion of the human population
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