The ixodid tick Haemaphysalis concinna Koch, 1844 is a proven vector of tick-borne encephalitis (TBE) virus and Francisella tularensis, the causative agent of tularaemia. In the present study, up-to-date maps depicting the geographical distribution and climate adaptation of H. concinna are presented. A dataset was compiled, resulting in 656 georeferenced locations in Eurasia. The distribution of H. concinna ranges from the Spanish Atlantic coast to Kamchatka, Russia, within the belt of 28-64° N latitude. H. concinna is the second most abundant tick species after Ixodes ricinus collected from birds, and third most abundant tick species flagged from vegetation in Central Europe. To investigate the climate adaptation of H. concinna, the georeferenced locations were superimposed on a high-resolution map of the Köppen-Geiger climate classification. A frequency distribution of the H. concinna occurrence under different climates shows three peaks related to the following climates: warm temperate with precipitation all year round, boreal with precipitation all year round and boreal, winter dry. Almost 87.3 % of all H. concinna locations collected are related to these climates. Thus, H. concinna prefers climates with a warm and moist summer. The remaining tick locations were characterized as cold steppes (6.2%), cold deserts (0.8%), Mediterranean climates (2.7%) or warm temperate climates with dry winter (2.9%). In those latter climates H. concinna occurs only sporadically, provided the microclimate is favourable. Beyond proven vector competence pathogen findings in questing H. concinna are compiled from the literature.

The castor bean tick, Ixodes ricinus (L.) (Ixodida: Ixodidae), is the principal vector of pathogens causing tick-borne encephalitis or Lyme borreliosis in Europe. It is therefore of general interest to make an estimate of the density of I. ricinus for the whole year at the beginning of the tick season. There are two necessary conditions for making a successful prediction: a long homogeneous time series of observed tick density and a clear biological relationship between environmental predictors and tick density. A 9-year time series covering the period 2009–2017 of nymphal I. ricinus flagged at monthly intervals in southern Germany has been used. With the hypothesis that I. ricinus density is triggered by the fructification of the European beech 2 years before, the mean annual temperature of the previous year, and the current mean winter temperature (December–February), a forecast of the annual nymphal tick density has been made. Therefore, a Poisson regression model was generated resulting in an explained variance of 93.4% and an error of ticks per (annual collected ticks/). An independent verification of the forecast for the year 2017 resulted in 187 predicted versus 180 observed nymphs per . For the year 2018 a relatively high number of 443 questing I. ricinus nymphs per is forecasted, i.e., a “good” tick year.

Ticks of the species Ixodes ricinus (L.) are the major vectors for tick-borne diseases in Europe. The aim of this study was to quantify the influence of environmental variables on the seasonal cycle of questing I. ricinus. Therefore, an 8-year time series of nymphal I. ricinus flagged at monthly intervals in Haselmühl (Germany) was compiled. For the first time, cross correlation maps were applied to identify optimal associations between observed nymphal I. ricinus densities and time-lagged as well as temporal averaged explanatory variables. To prove the explanatory power of these associations, two Poisson regression models were generated. The first model simulates the ticks of the entire time series flagged per 100 m, the second model the mean seasonal cycle. Explanatory variables comprise the temperature of the flagging month, the relative humidity averaged from the flagging month and 1 month prior to flagging, the temperature averaged over 4–6 months prior to the flagging event and the hunting statistics of the European hare from the preceding year. The first model explains 65% of the monthly tick variance and results in a root mean square error (RMSE) of 17 ticks per 100 m. The second model explains 96% of the tick variance. Again, the accuracy is expressed by the RMSE, which is 5 ticks per 100 m. As a major result, this study demonstrates that tick densities are higher correlated with time-lagged and temporal averaged variables than with contemporaneous explanatory variables, resulting in a better model performance.

BackgroundThe study describes the estimation of the spatial distribution of questing nymphal tick densities by investigating Ixodes ricinus in Southwest Germany as an example. The production of high-resolution maps of questing tick densities is an important key to quantify the risk of tick-borne diseases. Previous I. ricinus maps were based on quantitative as well as semi-quantitative categorisations of the tick density observed at study sites with different vegetation types or indices, all compiled on local scales. Here, a quantitative approach on the landscape scale is introduced.MethodsDuring 2 years, 2013 and 2014, host-seeking ticks were collected each month at 25 sampling sites by flagging an area of 100 square meters. All tick stages were identified to species level to select nymphal ticks of I. ricinus, which were used to develop and calibrate Poisson regression models. The environmental variables height above sea level, temperature, relative humidity, saturation deficit and land cover classification were used as explanatory variables.ResultsThe number of flagged nymphal tick densities range from zero (mountain site) to more than 1,000 nymphs/100 m2. Calibrating the Poisson regression models with these nymphal densities results in an explained variance of 72 % and a prediction error of 110 nymphs/100 m2 in 2013. Generally, nymphal densities (maximum 374 nymphs/100 m2), explained variance (46 %) and prediction error (61 nymphs/100 m2) were lower in 2014. The models were used to compile high-resolution maps with 0.5 km2 grid size for the study region of the German federal state Baden-Württemberg. The accuracy of the mapped tick densities was investigated by leave-one-out cross-validation resulting in root-mean-square-errors of 227 nymphs/100 m2 for 2013 and 104 nymphs/100 m2 for 2014.ConclusionsThe methodology introduced here may be applied to further tick species or extended to other study regions. Finally, the study is a first step towards the spatial estimation of tick-borne diseases in Central Europe.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-015-0015-7) contains supplementary material, which is available to authorized users.

Mosquitoes (Diptera: Culicidae) are important vectors for a wide range of pathogenic organisms. As large parts of the human population in developed countries live in cities, the occurrence of vector-borne diseases in urban areas is of particular interest for epidemiologists and public health authorities. In this study, we investigated the mosquito occurrence in the city of Vienna, Austria, in order to estimate the risk of transmission of mosquito-borne diseases. Mosquitoes were captured using different sampling techniques at 17 sites in the city of Vienna. Species belonging to the Culex pipiens complex (78.8 %) were most abundant, followed by Coquillettidia richiardii (10.2 %), Anopheles plumbeus (5.4 %), Aedes vexans (3.8 %), and Ochlerotatus sticticus (0.7 %). Individuals of the Cx. pipiens complex were found at 80.2 % of the trap sites, while 58.8 % of the trap sites were positive for Cq. richiardii and Ae. vexans. Oc. sticticus was captured at 35.3 % of the sites, and An. plumbeus only at 23.5 % of the trap sites. Cx. pipiens complex is known to be a potent vector and pathogens like West Nile virus (WNV), Usutu virus (USUV), Tahyna virus (TAHV), Sindbis virus (SINV), Plasmodium sp., and Dirofilaria repens can be transmitted by this species. Cq. richiardii is a known vector species for Batai virus (BATV), SINV, TAHV, and WNV, while Ae. vexans can transmit TAHV, USUV, WNV, and Dirofilaria repens. An. plumbeus and Oc. sticticus seem to play only a minor role in the transmission of vector-borne diseases in Vienna. WNV, which is already wide-spread in Europe, is likely to be the highest threat in Vienna as it can be transmitted by several of the most common species, has already been shown to pose a higher risk in cities, and has the possibility to cause severe illness.