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

摘要: Ticks of the species Ixodes ricinus (L.) are major vectors for tick-borne diseases in Europe. The aim this study was to quantify influence environmental variables on seasonal cycle questing I. ricinus. Therefore, an 8-year time series nymphal flagged at monthly intervals Haselmuhl (Germany) compiled. For first time, cross correlation maps were applied identify optimal associations between observed densities and time-lagged as well temporal averaged explanatory variables. To prove power these associations, two Poisson regression models generated. model simulates ticks entire per 100 m $$^2$$ , second mean cycle. Explanatory comprise temperature flagging month, relative humidity from month 1 month prior flagging, over 4–6 months event hunting statistics European hare preceding year. explains 65% tick variance results a root square error (RMSE) 17 . 96% variance. Again, accuracy is expressed by RMSE, which 5 ticks As result, demonstrates that higher correlated with than contemporaneous variables, resulting better performance.