Choropleth mapping of regional count data of Echinococcus multilocularis among red foxes in Lower Saxony, Germany.

In this paper, choropleth maps display the geographical distribution of Echinococcus multilocularis in red foxes in Lower Saxony. Areas of high prevalence of the infection in foxes and with high fox population density pose high risk for the human population for alveolar echinococcosis. Spatial statistical methods were used to analyse regional count data obtained from 5365 hunted or found-dead foxes. Spatial smoothing (of raw estimates of regional prevalences based on count data before mapping) was used because raw estimates can give an erratic impression of the spatial pattern of the infection. For smoothing, empirical Bayesian methods are used as an explorative spatial epidemiological tool. The resulting map showed the geographical variation of the estimated prevalences around a median at 9% and indicated the presence of spatial-trend effects. Based on this finding, conditional autoregressive spatial modelling for Freeman-Tukey transformed data was used as an inferential spatial epidemiological tool. There were significant additive linear and quadratic spatial-trend effects with elevated prevalences in the north and south and extreme values (prevalences>38%) for the south of Lower Saxony.