[Influence of meteorological factors on the activity of the adult taiga tick (Ixodes persulcatus Sch., Ixodinae) in St. Petersburg and its environs]

Ecology and prevalence of Borrelia burgdorferi s.l. in Ixodes ricinus (Acari: Ixodidae) ticks

Weather conditions greatly affect tick population densities and activity, on which depends the occurrence of tick-borne diseases (TBDs). During the spring months from 2017 to 2019, 1,357 specimens of Ixodes ricinus ticks were collected at 9 localities in the vicinity of Novi Sad (Serbia). The number of collected ticks varied considerably among the different sampling sites and years. Also, a statistically significant difference was found between months and observed number of ticks for each stadium. By statistical analysis of tick activity depending on microclimatic conditions, a positive and statistically significant relationship between temperature and the number of ticks for each life stage was established, but not for humidity. Dew had a statistically significant impact only on nymphs but not on adults. The infection rate of Borrelia burgdorferi s.l. was the highest in March (46.5-51.2%) and the lowest in May (32.9-34.8%). The highest prevalence was detected in males and the lowest in nymphs. Since there is a positive and statistically significant correlation between tick number and prevalence, the ability to provide weather-based predictions of the seasonal patterns of current tick activity is important for the risk assessment of TBDs such as Lyme borreliosis.

Food-Borne Transmission of Tick-Borne Encephalitis Virus—Spread, Consequences, and Prophylaxis

Tick-borne encephalitis (TBE) is the most common viral neurological disease in Eurasia. It is usually transmitted via tick bites but can also occur through ingestion of TBEV-infected milk and dairy products. The present paper summarises the knowledge of the food-borne TBEV transmission and presents methods for the prevention of its spread. The incidence of milk-borne TBE outbreaks is recorded in central, eastern, and north-eastern Europe, where Ixodes ricinus, Ixodes persulcatus, and/or Dermacentor reticulatus ticks, i.e., the main vectors of TBEV, occur abundantly. The growing occurrence range and population size of these ticks increases the risk of infection of dairy animals, i.e., goats, sheep, and cows, with viruses transmitted by these ticks. Consumers of unpasteurised milk and dairy products purchased from local farms located in TBE endemic areas are the most vulnerable to alimentary TBEV infections. Familial infections with these viruses are frequently recorded, mainly in children. Food-transmitted TBE can be monophasic or biphasic, and some of its neurological and psychiatric symptoms may persist in patients for a long time. Alimentary TBEV infections can be effectively prevented by consumption of pasteurised milk and the use of TBEV vaccines. It is recommended that milk and dairy products should be checked for the presence of TBE viruses prior to distribution. Protection of dairy animals against tick attacks and education of humans regarding the epidemiology and prophylaxis of TBE are equally important.

Long-term dynamics of Ixodes persulcatus (Acari: Ixodidae) abundance in the north-west of its range (Karelia, Russia)

The article presents the results of long-term observations of variations in the abundance of Ixodes persulcatus, carried out since 1982, in the middle taiga subzone of Karelia. Adult questing ticks were collected from vegetation following standard flagging procedures. The time series was evaluated by singular spectrum analysis. Correlation coefficients were calculated for the observed tick abundances and meteorological data (mean daily air temperature and precipitation) for the current year and preceding years. Analysis of the time series revealed the trend and harmonic components with periods of 8, 2.5 and 4 years. Around 83% of the total variance is explained by the first principal component, which governs the general vector of change-a gradual reduction in I. persulcatus abundance from 2003 to 2017. Correlations between tick abundance and climatic indices were observed in all years and were associated with both temperature and precipitation. The greatest number of significant coefficients was obtained for correlations between tick abundance and weather conditions in the preceding season. An equation was suggested where tick abundance is described by a linear function with four variables: mean air temperature in April and July, total precipitation in February, and annual number of days with temperatures above 5 °С. Thus, the observed long-term dynamics are characterized by the following key patterns: a sharp population rise early in the 2000s, some recent decline (stabilization) of the abundance, the presence of quasi-periodic cycles, and a close correlation between tick abundance and climatic variables.

Seasonal cycles of the TBE and Lyme borreliosis vector Ixodes ricinus modelled with time-lagged and interval-averaged predictors

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[Formula: see text], 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[Formula: see text]. The second model explains 96% of the tick variance. Again, the accuracy is expressed by the RMSE, which is 5 ticks per 100 m[Formula: see text]. 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.