Epidemiology has a long history of studying factors that affect the variability of the incidence or mortality of infectious and chronic diseases. Among those factors, geographical (or spatial) variations of health outcomes have played a crucial role in evaluating health care distribution and performance. Spatial variation in health outcomes has also provided evidence of patterns of dependence and level of noise in the data. More recently, time-series analyses have been used to examine the manner in which health variables vary over time. Spatiotemporal analyses have the additional benefits over purely spatial or time-series analyses because they allow the investigator to simultaneously study the persistence of patterns over time and illuminate any unusual patterns. The inclusion of space-time interaction terms may also detect data clustering that may be indicative of emerging environmental hazards or persistent errors in the data recording process.