Alveolar echinococcosis is a rare but fatal disease in humans and is caused by the fox tapeworm Echinococcus multilocularis. The densities of fox and grassland rodent populations and the interactions between them influence E. multilocularis transmission rates in Europe. Successful rabies control has caused fox populations and E. multilocularis prevalence rates to increase in many European countries. The potential increase of the infection pressure on the human population motivates the monitoring of the infection status of foxes over space and time. Detection of E. multilocularis antigen levels in fox faecal samples collected in the field might provide a pragmatic methodology for epidemiological surveillance of the infection status in wildlife hosts across large areas, as well as providing an indication of the spatial distribution of infected faeces contaminating the environment. In this paper, a spatial analysis of antigen levels detected in faeces collected in the Franche-Comté region of eastern France is presented. In Franche-Comté, rodent outbreaks have been observed to originate in areas rich in grassland. Spatial trends in fox infection levels were modelled here as a function of the composition ratio of grassland in the landscape derived from the CORINE land-cover map. Kriging models incorporating the grassland trend term were compared to a variety of models in which five alternative trend expressions were used: the alternative trend expressions included linear and quadratic polynomials on the x and y coordinates with and without a grassland term, and a constant mean model. Leave-one-out cross-validation indicated that the estimation errors of kriging with a trend models were significantly lower when the trend expression contained the grassland index term only. The relationship between observed and predicted antigen levels was strongest when the estimated range of autocorrelation was within the home range size of a single fox. The over-dispersion of E. multilocularis in foxes may therefore account for the majority of spatial autocorrelation locally, while regional trends can be successfully modelled as a function of habitat availability for intermediate hosts.