RESUMEN
The seasonal weather-driven activity of the tick Ixodes ricinus is frequently explored using multisite surveys. This study aimed to investigate the statistical modeling of seasonal trends in the activity of I. ricinus nymphs when both the influence of abiotic factors and spatial heterogeneity were taken into account. Time series data of abiotic covariates (temperature, relative humidity, rainfall and photoperiod) and nymphal tick counts were recorded on several sites in The Netherlands, Belgium and in France in 2008 and 2009. The sites were divided into two subsets which were used for model construction or model validation. A generalized linear mixed model was set up, with aggregated abiotic covariates as fixed effects, and the collection site as a random effect to account for the site-varying density in nymphs. A linear regression model was developed to estimate the site effect against the observed local abundance on each site. The activity patterns simulated from the weather and photoperiod covariates realistically reproduced the observed seasonal trends in nymphal tick activity. The fit between observed and simulated nymphal count time series was greatly improved when the site-specific local abundance in nymphs was included. Our modeling approach allows indicators of local tick abundance and the temporal modeling of I. ricinus activity to be combined. The model presented here can also be used to study scenarios on the temporal patterns of I. ricinus activity in the present and in the context of climate change.