Related Experiment Video
Updated: May 23, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
A review of spatial methods in epidemiology, 2000-2010
Amy H Auchincloss1, Samson Y Gebreab, Christina Mair
1Department of Epidemiology and Biostatistics, Drexel University School of Public Health, Philadelphia, Pennsylvania 19102, USA. aha27@drexel.edu
Abstract:
Understanding the impact of place on health is a key element of epidemiologic investigation, and numerous tools are being employed for analysis of spatial health-related data. This review documents the huge growth in spatial epidemiology, summarizes the tools that have been employed, and provides in-depth discussion of several methods. Relevant research articles for 2000-2010 from seven epidemiology journals were included if the study utilized a spatial analysis method in primary analysis (n = 207). Results summarized frequency of spatial methods and substantive focus; graphs explored trends over time. The most common spatial methods were distance calculations, spatial aggregation, clustering, spatial smoothing and interpolation, and spatial regression. Proximity measures were predominant and were applied primarily to air quality and climate science and resource access studies. The review concludes by noting emerging areas that are likely to be important to future spatial analysis in public health.
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Introduction to Epidemiology
Manipulation and Analysis
Bias in Epidemiological Studies
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Causality in Epidemiology
