Spatial visualization of multivariate datasets: an analysis of STD and HIV/AIDS diagnosis rates and socioeconomic context using ring maps.

Rates of sexually transmitted diseases (STDs) and human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) persist at elevated levels in the United States.1,2 Moreover, significant gender and racial/ethnic disparities in STD and HIV/AIDS rates remain, despite a commitment by public health leaders and the Healthy People 2010 initiative to eliminate health disparities.3 For example, the rate of primary- and secondary-stage syphilis (reported cases) is higher for men (7.8 per 100,000 population) than for women (1.4 per 100,000 population),2 while the rate of HIV diagnoses is higher among African Americans (66.6 per 100,000 population) than among white people (7.2 per 100,000 population).1 In accordance with program guidelines established by the Centers for Disease Control and Prevention (CDC), efforts to reduce STD and HIV/AIDS transmission and to address gender and racial/ethnic disparities in disease rates should be data driven.4–8 Disease surveillance data alone do not provide the contextual information necessary to guide the development of meaningful community interventions. Rather, successful STD and HIV/AIDS program planning and evaluation require the compilation, prioritization, and synthesis of wide-ranging information sets, including data on disease rates,1,2,5 modes of transmission,9–11 comorbid conditions,12–16 and treatment options and efficacy.13,16–18 Data on risk-taking behaviors;19–23 health-care-seeking and compliance behaviors;22,24–27 and sociocultural attitudes toward sex, STDs, and HIV/AIDS also are relevant to STD and HIV/AIDS programming efforts.9,20,28,29 Moreover, a growing body of literature cites a positive association between local disease rates and levels of socioeconomic disadvantage. For example, higher rates of syphilis, gonorrhea, and chlamydia have been found in impoverished areas of Massachusetts and Rhode Island;30 higher rates of AIDS have been noted in low-income neighborhoods in Los Angeles County in California31 and in census-block groups characterized by high levels of poverty in Massachusetts;32 and higher rates of HIV have been reported in high-poverty census tracts in Virginia.33 Based on such evidence, successful disease interventions must also consider the socioeconomic context of STDs and HIV/AIDS. Increasingly, geographic information systems (GISs) contribute critical spatial information to strengthen STD and HIV/AIDS program planning and evaluation processes.34–38 GIS visualization products—typically maps—yield valuable insight into relevant spatial distributions, patterns, and associations not readily apparent in tabled data. As useful as maps can be to STD/HIV/AIDS program planners and evaluators, the comparison and synthesis of information across multiple maps can prove cumbersome. A recent cartographic innovation, the ring map, facilitates the visual assessment of multivariate spatial data by depicting individual datasets as separate rings of information surrounding a base map of a particular geographic region of interest.39 In this way, a ring map effectively summarizes multiple layers of data, presenting an array of regional attributes (e.g., information about local population composition, health status, and/or socioeconomic conditions) in a single spatially referenced graphic. In this investigation, ring maps were created to spatially visualize county-level syphilis, gonorrhea, chlamydia, and HIV/AIDS diagnosis rate data for South Carolina, a state that ranks third in the nation in chlamydia rates per 100,000 women2 and seventh in the rate of HIV diagnoses (ninth overall, including Puerto Rico and the U.S. Virgin Islands).1 In addition, a ring map was developed to visually explore potential county-level associations between HIV/AIDS diagnosis rates and socioeconomic disadvantage in South Carolina.