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Tick-borne encephalitis (TBE) is peculiar due to its unstable dynamics with profound interannual fluctuations in case numbers – a phenomenon not well understood to date. Possible reasons – apart from variable human contact with TBE foci – include external factors, e.g. climatic forcing, autonomous oscillations of the disease system itself, or a combined action of both. Spectral analysis of TBE data from six regions of central Europe (CE) revealed that the ostensibly chaotic dynamics can be explained in terms of four superposed (quasi-)periodical oscillations: a quasi-biennial, triennial, pentennial, and a decadal cycle. These oscillations exhibit a high degree of regularity and synchrony across CE. Nevertheless, some amplitude and phase variations are responsible for regional differences in incidence patterns. In addition, periodic changes occur in the degree of synchrony in the regions: marked in-phase periods alternate with rather off-phase periods. Such a feature in the disease dynamics implies that it arises as basically diverging self-oscillations of local disease systems which, at intervals, receive synchronizing impulses, such as periodic variations in food availability for key hosts driven by external factors. This makes the disease dynamics synchronized over a large area during peaks in the synchronization signal, shifting to asynchrony in the time in between.

Tick-borne encephalitis is a serious arboviral infection with unstable dynamics and profound inter-annual fluctuations in case numbers. A dependable predictive model has been sought since the discovery of the disease. The present study demonstrates that four superimposed cycles, approximately 2·4, 3, 5·4, and 10·4 years long, can account for three-fifths of the variation in the disease fluctuations over central Europe. Using harmonic regression, these cycles can be projected into the future, yielding forecasts of sufficient accuracy for up to 4 years ahead. For the years 2016–2018, this model predicts elevated incidence levels in most parts of the region.

Recently, amorphous Hf-B-Si-C-N coatings found to demonstrate superior high-temperature oxidation resistance. The microstructure evolution of two coatings, Hf 7 B 23 Si 22 C 6 N 40 and Hf 6 B 21 Si 19 C 4 N 47 , annealed to 1500 °C in air is investigated to understand their high oxidation resistance. The annealed coatings develop a two-layered structure comprising of the original as-deposited film followed by an oxidized layer. In both films, the oxidized layer possesses the same microstructure with HfO 2 nanoparticles dispersed in an amorphous SiO x -based matrix. The bottom layer in the Hf 6 B 21 Si 19 C 4 N 47 coating remains amorphous after annealing while Hf 7 B 23 Si 22 C 6 N 40 recrystallized partially showing a nanocrystalline structure of HfB 2 and HfN nanoparticles separated by h-Si 3 N 4 and h-BN boundaries. The HfB 2 and HfN nanostructures form a sandwich structure with a HfB 2 strip being atomically coherent to HfN skins via (111)-Hf monolayers. In spite of the different bottom layer structure, the oxidized/bottom layer interface of both films was found to exhibit a similar microstructure with a fine distribution of HfO 2 nanoparticles surrounded by SiO 2 quartz boundaries. The high-temperature oxidation resistance of both films is attributed to the particular evolving microstructure consisting of HfO 2 nanoparticles within a dense SiO x -based matrix and quartz SiO 2 in front of the oxidized/bottom layer interface acting as a barrier for oxygen and thermal diffusion.

Twelve confirmed cases of equine granulocytic anaplasmosis (EGA) and five additional suspected cases, showing a compatible clinical history and specific IgG titres of 1280 or above, were recorded in the Czech Republic during the period 2002 to 2008. The diagnosis was based on clinical signs, the detection of Anaplasma phagocytophilum morulae in neutrophils in blood smears, serology and molecular methods. Pyrexia (39.8 to 41.3°C), depression, partial or total anorexia, limb oedema and icterus were the most frequently observed clinical abnormalities. Haematological examination revealed thrombocytopenia in all the horses, and mild anaemia and leucopenia in five of them. Several horses showed high titres of specific antibodies immediately after onset of the disease, suggesting that they had previously been exposed to A phagocytophilum. Genotyping of the A phagocytophilum strains distinguished two genetic variants, with divergence in the sequence of the ank gene of the bacterium, circulating in the Czech Republic.

Geographic information systems (GIS), their fundamental components and technologies are described. GIS is a computer-based system enabling the storage, integration, query, display and analysis of data using information on data location. Further, remote sensing (RS) methods and their application in landscape characterization are described. Landscape pattern analysis, combined with statistical analysis, allows the determination of landscape predictors of disease risk. This makes RS/GIS a powerful set of tools for disease surveillance, enabling the prediction of potential disease outbreaks and targeting intervention programs. The ‘pre-GIS era’ is briefly described including the early mapping of tick distribution, analyses and the display of biogeographical and medical data. The theory of natural focality of diseases (NFD) is explained and its significance in tick-borne diseases (TBD) research is discussed. Many problems of tick ecology and TBD epidemiology and epizootology have been addressed by means of GIS and examples of these studies are presented and discussed.

The geographic/temporal pattern of cases of tick-borne encephalitis (TBE) registered in the Czech Republic since 1970 was analysed to verify the surmise of a global warming effect. Using a geographic information system, over 8,700 notified places of infection were pin-pointed on a map and overlaid with a digital elevation model to estimate the vertical distribution of the cases. Series of yearly disease ceilings (assessed alternatively as the respective maximum altitude or mean altitudes of the upper 5 or 10 cases) were tested against the null hypothesis of random elevation course and analysed for correlation with concomitant factors (yearly TBE incidence rate, mean yearly temperature, population density of small rodents and roe deer). Statistical tests proved that the TBE ceiling has gradually moved upwards in the course of the last three decades. The average rate of ascension within this period was approx. 5.4 +/- 1.7 m yearly, which corresponds well with concurrent mean temperature rising of approx. 0.036 +/- 0.007 degrees C yearly, and the vertical temperature gradient of 0.0065 +/- 0.0004 degrees C m(-1). The TBE-ceiling estimates significantly correlated with TBE-incidence data and the mean yearly temperature recorded 1-2 years earlier. Although TBE incidence correlated with rodent population density that was observed 1-2 years earlier, the TBE ceiling does not seem to be influenced by rodent population dynamics nor did the population dynamics correlate with mean yearly temperatures. TBE incidence as well as mean altitudes of the upper 10 cases also correlated with official data on harvested roe deer. Overall, the fluctuations of TBE incidence and TBE ceiling proved to be synchronous processes that correspond with temperature changes. Although the dependence of TBE on temperature is not a direct one and various factors could be involved, an impact of climate warming on the vertical disease distribution in Central Europe is evident.

An array of 12 20 x 20 m quadrats in a mixed forest near Poteply, Central Bohemia, Czech Republic, was investigated for the abundance and spatial distribution of host-questing Ixodes ricinus nymphs and their infection with borreliae. Tick densities were estimated by flagging and their borrelia infection status was determined by direct immunofluorescence. While the tick population appeared to be continuous and homogeneous based on quadrat counts, their infection with borreliae evinced a mosaic pattern. The nymphal infection rates ranged between 1.6 and 10.5% (mean = 6.0%) with significant differences between adjacent quadrats. Home ranging of small rodents (Apodemus flavicollis and Clethrionomys glareolus) inhabiting the forest seems to be responsible for the spatial pattern of borrelial infection.

Efficient tick and tick-borne disease control is a major goal in the efforts to improve the livestock industry in developing countries. To gain a better understanding of the distribution and abundance of livestock ticks under changing environmental conditions, a country-wide field survey of tick infestations on indigenous cattle was recently carried out in Tanzania. This paper evaluates four models to generate tick predictive maps including areas between the localities that were surveyed. Four techniques were compared: (1) linear discriminant analysis, (2) quadratic discriminant analysis, (3) generalised regression analysis, and (4) the weights-of-evidence method. Inter-model comparison was accomplished with a data-set of adult Rhipicephalus appendiculatus ticks and a set of predictor variables covering monthly mean temperature, relative humidity, rainfall, and the normalised difference vegetation index (NDVI). The data-set of tick records was divided into two equal subsets one of which was utilised for model fitting and the other for evaluation, and vice versa, in two independent experiments. For each locality the probability of tick occurrence was predicted and compared with the proportion of infested animals observed in the field; overall predictive success was measured with mean squared difference (MSD). All models exhibited a relatively good performance in configurations with optimised sets of predictors. The linear discriminant model had the least predictive success (MSD>or=0.210), whereas the accuracy increased in the quadratic discriminant (MSD>or=0.197) and generalised regression models (MSD>or=0.173). The best predictions were gained with the weights-of-evidence model (MSD>or=0.141). Theoretical as well as practical aspects of all models were taken into account. In summary, the weights-of-evidence model was considered to be the best option for the purpose of predictive mapping of the risk of infestation of Tanzanian indigenous cattle. A detailed description of the implementation of this model is provided in an annex to this paper.