In detecting outbreaks of infectious disease, the time model has very much preceded the space model. Most public health agencies rely very heavily on time series of traditional and maybe syndromic health data (laboratory confirmed cases of illnesses as well as secondary data such as emergency department visits), looking for atypical temporal patterns. But few integrate spatial information (even fewer beyond running SatScan), even though statisticians and geographers have shown through research and simulations that outbreaks could be detected with improved timeliness and sensitivity/specificity (fewer false positives or false negatives) if spatial information were included. Many of the concepts in this paper are very relevant to outbreak detection, such as idea of a space-time path in a “lifestyle.” Either way, incorporating both space and time into analysis/research seems to be a real challenge in computational power, in model complexity, and in visualization. Even though this paper was written over ten years ago and made some very concrete suggestions for moving forward in time geography, I’m not sure how far we’ve come.
-Kathryn