title: Spatio-temporal epidemiology: principles and opportunities.
abstract: 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.
authors: Graduate Program in Public Health, Department of Preventive Medicine, Stony Brook University, HSC L3 Rm 071, Stony Brook, NY 11794-8338, USA. Jaymie.meliker@stonybrook.edu
authors: Jaymie R
authors: JR
authors: Meliker
authors: Chantel D
authors: CD
authors: Sloan
mesh_terms: D003627:Data Interpretation, Statistical; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D062665:Epidemiological Monitoring; D040362:Geographic Information Systems; D062306:Geography, Medical / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D062211:Spatio-Temporal Analysis