Abstract: HIV/AIDS and STD Co-Morbidity Assessment with the Use of Case-Based Registry Matching, California, 2007 (2010 National STD Prevention Conference)

Tuesday, March 9, 2010: 11:30 AM

International Ballroom A/B/C/D (M2) (Omni Hotel)

Jennifer Brodsky, MPH¹, Michael Samuel, DrPH², Mark Damesyn, DrPH³, Peter Kerndt, MD, MPH⁴, Kyle Bernstein, PhD, ScM⁵ and Gail Bolan, MD¹, 1Sexually Transmitted Disease Control Branch, California Department of Public Health, Richmond, CA, 2Epidemiology and Surveillance Section, California Department of Public Health, STD Control Branch, Richmond, CA, 3Office of AIDS, California Department of Public Health, Sacramento, CA, 4STD Program, Los Angeles County Department of Public Health, Los Angeles, CA, 5STD Prevention and Control Services Program, San Francisco Department of Public Health, San Francisco, CA

Audio File Recorded presentation

Background: Estimates of STD-HIV/AIDS co-morbidity are critical for targeting program collaboration and service integration efforts; however, such data are not collected through standard HIV and STD case-based surveillance.

Objectives: Analyze co-morbidity of HIV/AIDS and chlamydia (CT), gonorrhea (GC), and primary and secondary (P&S) syphilis using California HIV/AIDS and STD case reports.

Methods: Living HIV/AIDS cases were matched to STD cases diagnosed in 2007 using a deterministic algorithm including first and last names, birthdate, sex, and race. Co-morbidity data were stratified by sociodemographic, provider, and risk characteristics.

Results: In 2007, there were 97,693 persons living with HIV/AIDS (PLWH/A), 31,193 GC cases, 142,997 CT cases, and 2,066 P&S syphilis cases. HIV/AIDS prevalence was higher among male STD cases compared with female cases: GC, 9.0% versus 0.2%; P&S syphilis, 39.1% versus 1.7%; CT, 3.5% versus 0.1%, respectively. Among PLWH/A, STD incidence was also higher among males compared with females: GC, 1.6% versus 0.3%; P&S syphilis, 0.9% versus 0.02%; CT, 1.6% versus 1.0%, respectively. HIV/AIDS prevalence was highest among male GC cases aged 40-49 years (21.9%) and 50-59 years (21.3%); white males (18.3%); and males living in San Francisco (28.9%). Annual GC incidence among PLWH/A was highest among younger males (7.7% among ages 13-19; 5.6% among ages 20-29), and varied only slightly from 1.6% among white to 1.8% among African-American males. Among HIV/AIDS-GC co-morbid cases (n=964 with data), the highest number of GC cases was among those diagnosed with HIV/AIDS in private physician offices (n=336; 34.9%), adult HIV clinics (n=246; 25.5%), other clinics (n=110; 11.4%), and STD clinics (n=93; 9.6%).

Conclusions: Matching existing HIV/AIDS and STD data was a powerful, cost-efficient method for identifying populations and settings with high rates of STD-HIV/AIDS co-morbidity.

Implications for Programs, Policy, and/or Research: It is essential to utilize existing data to cost-efficiently target program integration resources, including HIV/STD testing, for populations with high co-morbidity rates.

See more of: HIV/STD Co-Infection: Epidemiology
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