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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. [ABSTRACT FROM AUTHOR]

Digital maps, particularly displayed on virtual globes, will represent the most important source of geographical knowledge in the future. The best known of these virtual globes is Google Earth, whose use in teaching at schools and universities is now common practice. As the first result of a series of forthcoming digital tick maps, the worldwide distribution of the marsh tick Dermacentor reticulatus is shown on Google Earth. For this purpose, various distribution maps of D. reticulatus were compiled, including digitized expert maps and a map of suitable habitats compiled with a species distribution model (SDM). A random forest model that estimates suitable habitats by combining information from tick observations, bioclimatic variables, altitude, and land cover was chosen for the latter. In the Google Earth application, the following maps can be selected: a historical expert map, a current expert map, a SDM predicted habitat suitability map, a combined expert-habitat suitability map (considered to be the best representation of the current distribution of D. reticulatus), and a map of rasterized tick locations. Users can overlay these maps according to their own requirements or combine it with other Google Earth content. For example, a comparison of the historical with the current expert map shows the spread of D. reticulatus over the past few decades. Additionally, high-resolution city maps of Bilbao (Spain), Grenoble (France), Berlin (Germany), Wrocław (Poland), Budapest (Hungary), Bucharest (Romania), and Tomsk (Russia) demonstrate the urban distribution of D. reticulatus in public parks, fallow land, and recreational areas. The Google Earth application, developed using the Keyhole Markup Language (KML), also contains fact sheets on biology, ecology, seasonal activity, and vector competence of D. reticulatus. This information has been prepared in a compact and easily understandable way for the target group, i.e. scientists from various disciplines, students, and lay people interested in the geographical distribution of ticks. [ABSTRACT FROM AUTHOR]

Individual-based or population-level simulation approaches are often employed alternatively in eco-epidemiological modeling. In this paper, we introduce an original coupling approach applied to bubonic plague zoonotic infection in the Pre-Balkhash focus (central Asia), with main host Rhombomys opimus (Rodentia: Gerbillidae) and vector its associated ectoparasite flea Xenopsylla gerbilli minax . An Individual-Based Model (IBM) is first developed as a Multi-Agent System (MAS), addressing the seasonally forced internal dynamics of a typical burrow system based upon individual processes and interaction rules of the host-vector parasitoid system. Key population parameters and incidence functions are derived from simulations on the IBM and introduced in a second stochastic Population-Level Model (PLM), operating at the level of a metapopulation composed of interacting communities occupying burrow systems. The methodology facilitates knowledge integration and encourages bridging scales at which determinant contagion processes occur. Through simulations, we bring new insights about conditions for the local persistence of plague in a seasonally constrained environment. Under the seasonal scenario where half of the fleas overwinter in an active state, the introduction of the plague pathogen in spring in a metapopulation composed of 20 communities leads in one case out of two to epizootics surviving the first winter, while the infection has a 5% chance of passing the second winter. If the metapopulation is extended to 70 communities, simulations suggest the same 5% chance is estimated for plague persisting almost 4 years. Optimal vector community sizes or host dispersal intensities for the persistence of epizootics are also highlighted by sensitivity analyses. [ABSTRACT FROM AUTHOR]

The goal of this paper is to present up-to-date maps depicting the geographical distribution of Dermacentor species in Europe based on georeferenced sampling sites. Therefore, a dataset was compiled, resulting in 1286 D. marginatus (Sulzer, 1776) and 1209 D. reticulatus (Fabricius, 1794) locations. Special emphasis is given to the region of the European Alps depicting a presumable climate barrier of the mountains and to overlaps in the distribution of both species as well as on the situation in eastern European countries. For the latter newly described Dermacentor findings comprise 59 locations in Romania and 62 locations in Ukraine. The geographical distributions of both species in Europe range from Portugal to Ukraine (and continue to the east of Kazakhstan). Although it is well known that D. marginatus is adapted to a warmer and drier climate at more southern latitudes and D. reticulatus to a moderately moist climate at more northern latitudes, the distribution limits of both species were not well known. Here, the northern and southern distribution limits for both species in Europe, as determined from the georeferenced database, were specified for D. marginatus by the belt of 33–51° N latitude and for D. reticulatus by the belt of 41–57° N latitude. Thus, overlapping species distributions were found between 41° N and 51° N. [ABSTRACT FROM AUTHOR]

In spring 2019, forecasts of the incidence of tick-borne encephalitis (TBE) for the next 2 years, i.e. 2019 and 2020, were made for the first time. For this purpose, negative binomial regression models with 4–5 predictors were fitted to the time series of annual human TBE incidences from Austria, Germany, and Switzerland. The most important predictor for TBE incidences is the fructification index of the European beech (Fagus sylvatica) 2 years prior as a proxi for the intensity of the TBE virus transmission cycle. These forecasts were repeated in spring 2020 after the updated predictors and the confirmed TBE cases for 2019 became available. Forecasting TBE incidences for 2020 and 2021 results in 156 ± 19 and 131 ± 23 TBE cases for Austria, 663 ± 95 and 543 ± 112 TBE cases for Germany as well as 472 ± 56 and 350 ± 62 TBE cases for Switzerland. The newly implemented operational TBE forecasts will be verified every year with confirmed TBE cases. An initial verification for 2019 demonstrates the high reliability of the forecasts. [ABSTRACT FROM AUTHOR]

The forecast of human tick-borne encephalitis (TBE) incidence for the next years has been on the research agenda of epidemiologists since the discovery of this tick-borne zoonosis. Based on models to explain the trend as well as the low- and high-frequency oscillations in the Austrian TBE incidence series, TBE forecasts for Austria, Germany and Switzerland are presented here. For this purpose, generalized linear models (GLMs) of type negative binomial regression were calibrated with the TBE incidences of the period 1991–2018 to forecast the TBE incidences 2019 and 2020. The GLMs require only 4–5 predictors, 2 of which are large-scale synchronized over Central Europe and used for all 3 countries. Predictors used include the demographic parameters total population and net migration rate, the Scandinavian index which describes the large-scale atmospheric circulation patterns, the fructification index of the European beech (Fagus sylvatica) 2 years prior as a proxy for the intensity of the TBE virus transmission cycle, and the national TBE vaccination coverage. Since an official time series of TBE vaccination coverage is only available for Austria, the missing TBE vaccination coverages of Germany and Switzerland were reconstructed and presented as the first results. Model verification results in explained variances of 76% for Austria, 84% for Germany, and 89% for Switzerland. Thus, the best model fit was determined for the Swiss GLM which is able to predict the TBE incidence with a root-mean-square error of RMSE = 25 cases (19% of the mean TBE incidence 1991–2018 or 7% of the TBE incidence of 2018). Forecasting TBE incidences for 2019 and 2020 results in 92 ± 12 and 142 ± 26 TBE cases for Austria, 417 ± 71 and 670 ± 168 TBE cases for Germany as well as 235 ± 30 and 465 ± 91 TBE cases for Switzerland. [ABSTRACT FROM AUTHOR]