Geographical information systems (GIS) have been widely used to map disease distribution. Spatial statistics and modelling have been complementary applied to detect spatial and temporal patterns and to correlate them to environmental variables obtained from remote sensed data. Displaying the spatial variations of parasite incidence help to detect where the disease is particularly prevalent, and this can be done at various spatial and temporal scales. Correlating those patterns to environmental factors helps to form hypotheses on the mechanistic processes that may prevail and explain transmission. This eventually leads to designing quasi-experiments such as comparative studies to challenge those hypotheses. The increasing availability of free open source GIS and statistic software products, the larger diversity of mathematical methods enabling spatial data analysis and the free access to a large number of satellite and environment databases have made such approach more and more popular. Most studies on cestodes based explicitly on a spatial approach deal with sea and freshwater parasites. Surprisingly few deal with cestode terrestrial pathogens of public health importance such as the genus Echinococcus and very few on Taenia sp. and cysticercosis. The present talk illustrates how parasite and environmental data combined can be used to increase our understanding of cestod transmission and subsequently help to implement evidence based control. We briefly describe how point pattern analysis and prevalence data may aid to quantify disease aggregation, and illustrate with examples how spatial approach of disease distribution, environmental variables and population genetics can help to characterize transmission systems. We also review studies where spatial analyses have been used to better understand cysticercosis distribution and present ongoing research on this issue in China.