Background: Richmond is an independent city located in central Virginia, with a 2007 gonorrhea rate approximately 7.5 times the state average and up to 7.5 times that of neighboring jurisdictions. These large differences in gonorrhea rates within a relatively small metropolitan area lend themselves to further study of the associated geographic and social factors.
Objectives: Determine how gonorrhea rates in the Richmond metropolitan area differ by neighborhood characteristics as captured by area-based socioeconomic measures.
Methods: Data on gonorrhea cases from 2000 to 2007 were collected as part of routine STD surveillance activities. Residential addresses were geocoded and aggregated to the census tract and block group level, and used to calculate area-specific rates of disease. These rates were then linked to data on area-based socioeconomic measures (ABSMs) derived from the 2000 U.S. Census (e.g. poverty, education, unemployment, racial composition). ArcGIS software was used for exploratory geographic visualization of gonorrhea rates and ABSM distribution in the region. Poisson regression models will be used to further evaluate the relationship between ABSMs and gonorrhea incidence rates.
Results: A total of 8,643 gonorrhea cases in the Richmond metropolitan area were included in the analyses. Unadjusted incidence rates of gonorrhea varied from 0 to 2,279 per 10,000 by census block group. Geographic visualization indicated correlation between high incidence rates and high levels of poverty, unemployment, and race. Poisson regression models will statistically quantify the extent to which these ABSMs are associated with gonorrhea rates.
Conclusions: Contextual factors such as ABSMs may provide a greater understanding of gonorrhea incidence and geographic distribution.
Implications for Programs, Policy, and/or Research: Identification of neighborhood factors pertinent to the spread of gonorrhea and other STDs may allow for better focusing of STD prevention efforts, including targeting screening activities, which may help to alleviate the spread of disease as well as conserve limited public health resources.