Spatial Epidemiology: Where Have We Come in 150 Years?

Abstract

Modern epidemiology is founded on a tradition of spatial analysis. The genesis of this discipline can be traced to the classic work of John Snow and the Broad Street pump. During the 1850s, cholera outbreaks were an important cause of morbidity and mortality amongst the inhabitants of London. Using simple dot maps and visualization, Snow provided compelling evidence that cases were clustered and that fecal-contaminated drinking water might be the cause of some cholera outbreaks. During the intervening 150 years, spatial epidemiology (alternatively called landscape epidemiology and more broadly, medical geography) has developed into a field within its own right. During the past two decades, advances in geographic information systems and statistical methods for analyzing spatially-referenced health data has allowed epidemiologists to routinely perform spatial analyses. Some of the most beneficial advances in spatial epidemiology have been in the areas of data visualization, detection of disease clusters, identification of spatial risk factors, application of predictive models, and the routine incorporation of GIS into disease surveillance programs. In this chapter, approaches used in spatial epidemiology will be described. Some specific techniques that are currently popular in the discipline will be presented. Several case studies will be used to highlight the application of these techniques within the field of spatial epidemiology and to illustrate the potential value of this discipline to public health and homeland security. The chapter will conclude by considering some of the major obstacles that remain to the consolidation of spatial analysis as a foundation of modern epidemiology, including the availability and quality of spatial disease data, information on the distributions of the populations at-risk, and integration of methods seamlessly into epidemiologic software packages.KeywordsMedical geographyepidemiologyGISpublic healthhomeland security