Space-time analysis of disease data has historically involved the search for patterns in aggregated data to identify how regions of high and low risk change through time. Space-time analysis of aggregated data has great value, but represents only a subset of space-time epidemiologic applications. Technological advances for tracking and mapping individuals (e.g., global positioning systems) have introduced mobile populations as an important element in space-time epidemiology. We review five domains critical to the developing field of spatio-temporal epidemiology: (1) spatio-temporal epidemiologic theory, (2) selection of appropriate spatial scale of analysis, (3) choice of spatial/spatio-temporal method for pattern identification, (4) individual-level exposure assessment in epidemiologic studies, and (5) assessment and consideration of locational and attribute uncertainty. This review provides an introduction to principles of space-time epidemiology and highlights future research opportunities.
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