Geospatial Science and Health: Overview of Data and Methods

This chapter explores the role of geospatial science in health research. First, geospatial technology and data considerations are discussed, focusing on spatial resolution and geocoding techniques. Due to privacy concerns, health data are often aggregated into areal units, resulting in limitations related to data aggregation and the Modifiable Areal Unit Problem (MAUP). Geographic Information Systems (GIS) have tools for addressing the MAUP and other challenges, including spatial autocorrelation that arises due to the tendency of spatial data to cluster. Part two covers mapping considerations for health-related data, focusing on thematic maps for various data types. In part three, applications in health research are discussed in relation to two goals: (i) disease mapping and descriptive analysis and (ii) the assessment of spatial relationships. A primary goal in geospatial health analyses is to identify the patterning of diseases. Disease mapping and cluster detection are well-cited approaches in disease surveillance and descriptive analysis. Another goal in geospatial health research is identifying relationships that influence spatial patterns. Place-based social and environmental factors are often analyzed alongside health data using geospatial statistical analysis. Throughout analysis, attention must be placed on protecting patient privacy. Methods for preserving point-level data privacy while producing meaningful results are discussed.