The authors present findings from two landscape epidemiology studies of chronic wasting disease (CWD) in northern Colorado mule deer (Odocoileus hemionus). First, the effects of human land use on disease prevalence were explored by formulating a set of models estimating CWD prevalence in relation to differences in human land use, sex and geographic location. Prevalence was higher in developed areas and among male deer suggesting that anthropogenic influences (changes in land use), differences in exposure risk between sexes and landscape-scaled heterogeneity are associated with CWD prevalence. The second study focused on identifying scales of mule deer movement and mixing that had the greatest influence on the spatial pattern of CWD in north-central Colorado. The authors hypothesised that three scales of mixing - individual, winter subpopulation and summer subpopulation - might control spatial variation in disease prevalence. A fully Bayesian hierarchical model was developed to compare the strength of evidence for each mixing scale. Strong evidence was found indicating that the finest mixing scale corresponded best to the observed spatial distribution of CWD prevalence. This analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight into the epidemiology of wildlife diseases when process data are sparse or unavailable.