190909 Block group characteristics and gonorrhea incidence rates in Richmond, Virginia, from 2000 to 2007

Tuesday, October 28, 2008: 12:35 PM

Qian Zhang, MS , Department of Epidemiology & Community Health, Virginia Commonwealth University, Richmond, VA
Oana Vasiliu, MD, MPH , Virginia Department of Health, Health Informatics & Integrated Surveillance Systems, Division of Disease Prevention ,Virginia Department of Health, Richmond, VA
Chris Delcher, MS , Virginia Department of Health, Richmond, VA
Jeff Stover, MPH , Health Informatics & Integrated Surveillance Systems Division of Disease Prevention Virginia Department of Health, Virginia Department of Health, Richmond, VA
Background: Sexually Transmitted Infections (STI) are among the leading causes of health disparities in the U.S. We examined neighborhood characteristics associated with gonorrhea incidence in a city with historically high STI rates. Methods: We analyzed reported gonorrhea diagnoses (n=9,979) between 2000 and 2007 in the city of Richmond, Virginia. Gonorrhea cases were geocoded and mapped to block groups (n=163). Spatial analyses were conducted to identify core areas and calculate gonorrhea incidence rates for each block group. Area-based socioeconomic measures (ABSMs) were created by using 2000 census data and compared across the block groups with high, medium and low gonorrhea incidence rates. Results: The average yearly incidence rate of gonorrhea in Richmond was 681 per 100,000. Of the total number of cases, 85.5% were under the age of 35, and 84.4% were Black. Two block groups with very high incidence rates (8 and 16 times the average) were identified. The block groups with high gonorrhea incidence rates (over 867 per 100,000) were significantly associated with larger population percentages below poverty line, lower median household income, higher percentages of less than high school education, and higher Z score for Townsend Index when compared to those with low and medium incidence rates (p<0.001). Discussion: Spatial analyses at the block group level combined with ABSMs provide additional demographic details that can improve STI surveillance and interventions. More analyses at small levels of geographic detail should occur to assist with refining STI prevention targeting.

Learning Objectives:
Identify gonorrhea core areas and socioeconomic measures associated with high incidence rates

Keywords: STD, Geographic Information Systems

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have assisted epidemiologic analyses of enhanced surveillance STD and mobility data including Virginia and Richmond City in the Division of Disease Prevention at Virginia Department of Health.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.