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A density map of the tick-borne encephalitis and lyme borreliosis vector ixodes ricinus (acari: ixodidae) for Germany


Brugger, Katharina; Boehnke, Denise; Petney, Trevor; Dobler, Gerhard; Pfeffer, Martin; Silaghi, Cornelia; Schaub, Günter A; Pinior, Beate; Dautel, Hans; Kahl, Olaf; Pfister, Kurt; Süss, Jochen; Rubel, Franz (2016). A density map of the tick-borne encephalitis and lyme borreliosis vector ixodes ricinus (acari: ixodidae) for Germany. Journal of Medical Entomology, 53(6):1292-1302.

Abstract

The castor bean tick Ixodes ricinus (L.) is the principal vector for a variety of viral, bacterial, and protozoan pathogens causing a growing public-health issue over the past decades. However, a national density map of I. ricinus is still missing. Here, I. ricinus nymphs in Germany were investigated by compiling a high-resolution map depicting the mean annually accumulated nymphal density, as observed by monthly flagging an area of 100 m(2) Input data comprise ticks collected at 69 sampling sites. The model domain covers an area of about 357,000 km(2) (regional scale). Two negative binomial regression models were fitted to the data to interpolate the tick densities to unsampled locations using bioclimatic variables and land cover, which were selected according to their significance by the Akaike information criterion (AIC). The default model was fitted to the complete dataset resulting in AIC = 842. An optimized model resulted in a significantly better value of AIC = 732. Tick densities are very low in urban (green) areas. Maximum annual densities up to 1,000 nymphs per 100 m(2) are observed in broad-leaved forests. The tick maps were verified by leave-one-out cross-validation. Root mean square errors of RMSE = 137 and RMSE = 126 nymphs per 100 m(2) were estimated for the two models, respectively. These errors are of the order of the interannual variation of the tick densities. The compilation of a high-resolution density map of unfed nymphal I. ricinus for Germany provides a novel, nationwide insight into the distribution of an important disease vector.

Abstract

The castor bean tick Ixodes ricinus (L.) is the principal vector for a variety of viral, bacterial, and protozoan pathogens causing a growing public-health issue over the past decades. However, a national density map of I. ricinus is still missing. Here, I. ricinus nymphs in Germany were investigated by compiling a high-resolution map depicting the mean annually accumulated nymphal density, as observed by monthly flagging an area of 100 m(2) Input data comprise ticks collected at 69 sampling sites. The model domain covers an area of about 357,000 km(2) (regional scale). Two negative binomial regression models were fitted to the data to interpolate the tick densities to unsampled locations using bioclimatic variables and land cover, which were selected according to their significance by the Akaike information criterion (AIC). The default model was fitted to the complete dataset resulting in AIC = 842. An optimized model resulted in a significantly better value of AIC = 732. Tick densities are very low in urban (green) areas. Maximum annual densities up to 1,000 nymphs per 100 m(2) are observed in broad-leaved forests. The tick maps were verified by leave-one-out cross-validation. Root mean square errors of RMSE = 137 and RMSE = 126 nymphs per 100 m(2) were estimated for the two models, respectively. These errors are of the order of the interannual variation of the tick densities. The compilation of a high-resolution density map of unfed nymphal I. ricinus for Germany provides a novel, nationwide insight into the distribution of an important disease vector.

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3 citations in Web of Science®
2 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:05 Vetsuisse Faculty > Institute of Parasitology
04 Faculty of Medicine > Institute of Parasitology
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
600 Technology
Language:English
Date:7 August 2016
Deposited On:12 Aug 2016 11:46
Last Modified:08 Dec 2017 20:10
Publisher:Oxford University Press
ISSN:0022-2585
Publisher DOI:https://doi.org/10.1093/jme/tjw116
PubMed ID:27498885

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