In the past decade, various social network theories have been created and implemented to uncover the driving factors of the HIV epidemic across the world. Several of these theories build on the basic "mass-effect" model of disease transmission, and take into consideration an additional layer of covariates to characterize complex human behaviors. The resulting models have provided the scientific community with additional insights into HIV dynamics in human populations.
In the same context, there is a belief that individuals who believe that they are at risk would travel longer distances to receive testing and counseling due to the level of social stigma attached to being HIV positive in certain areas. My objective was to determine if this social phenomenon occurs in Pennsylvania, and if it does, if it is limited to a subset(s) of the overall tested population and what factor(s) is driving this behavior.
Geospatial analyses of roughly 7 years of HIV testing data were performed to calculate the actual distance traveled and the distance to the closest clinic for each tested individual. The resulting distance dataset was evaluated with respect to covariates such as differences in risk behavior, test result status and geographical regions.
Results/Conclusions
Preliminary calculations have shown that individuals who reside in PA would travel an average excess distance of 15 mi. to get tested. In addition, based on a few regression analyses there might be significant differences in excess distance traveled among different risk behavior groups (MSM, IDU, Heterosexual, Perinatal). However, there does not seem to be a significant difference between individuals who tested positive, and those who tested negative.
Excess distance traveled is based on the actual distance traveled minus the distance to the closest testing site with respect to each individual's home residence. So for an individual who got tested at the nearest clinic with relation to where he/she lives, the excess distance will be zero. Distance between two points is derived from greater arc distance calculations based on the global coordinates given by the centroids of the listed zip codes of residence and clinical sites.
