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

Jeffrey M SwitchenkoJacky M JenningsLance A Waller
Published in: Journal of geographical systems (2020)
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.
Keyphrases
  • healthcare
  • public health
  • men who have sex with men
  • magnetic resonance imaging
  • electronic health record
  • machine learning
  • health information
  • quality improvement
  • breast cancer risk