Exploring spatially varying demographic associations with gonorrhea incidence in Baltimore, Maryland, 2002–2005

Jeffrey M. Switchenko (), Jacky M. Jennings and Lance A. Waller
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Jeffrey M. Switchenko: Emory University
Jacky M. Jennings: Johns Hopkins University
Lance A. Waller: Emory University

Journal of Geographical Systems, 2020, vol. 22, issue 2, No 2, 216 pages

Abstract: Abstract The ability to establish spatial links between gonorrhea risk and demographic features is an important step in disease awareness and more effective prevention techniques. Past spatial analyses focused on local variations in risk, but not on spatial variations in associations with demographics. We collected data from the Baltimore City Health Department from 2002 to 2005 and evaluated demographic features known to be associated with gonorrhea risk in Baltimore, by allowing spatial variation in associations using Poisson geographically weighted regression (PGWR). The PGWR maps revealed variations in local relationships between race, education, and poverty with gonorrhea risk which were not captured previously. We determined that the PGWR model provided a significantly better fit to the data and yields a more nuanced interpretation of “core areas” of risk. The PGWR model’s quantification of spatial variation in associations between disease risk and demographic features provides local and demographic structure to core areas of higher risk.

Keywords: Geographically weighted regression; Spatial analysis; STIs; Core area (search for similar items in EconPapers)
JEL-codes: C18 C31 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10109-020-00321-7

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