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.
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Funding
Dr. Switchenko was funded by the Biostatistics in Genetics, Immunology, and Neuroimaging (BGIN) training grant, a predoctoral training grant from the National Institute of General Medicine Science (NIGMS). Dr. Jennings was funded for this work by the National Institute of Drug Abuse (Grant Number KO1 DA022298-01A1).
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10109_2020_321_MOESM1_ESM.tif
Supplemental Fig 1 Maps of observed SIR (a) and predicted SIR (b) from 2002 to 2003; maps of observed SIR (a) and predicted SIR (b) from 2004 to 2005 (TIFF 26367 kb)
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Switchenko, J.M., Jennings, J.M. & Waller, L.A. Exploring spatially varying demographic associations with gonorrhea incidence in Baltimore, Maryland, 2002–2005. J Geogr Syst 22, 201–216 (2020). https://doi.org/10.1007/s10109-020-00321-7
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DOI: https://doi.org/10.1007/s10109-020-00321-7