Linking STD and HIV Morbidity and Risk Behaviors in Indiana

1. Linking STD and HIV Morbidity and Risk Behaviors in Indiana James D. Beall, MA Sr. Public Health Advisor Indiana State Department of Health

2. OASIS Outcomes Assessment Through Systems of Integrated Surveillance grant awarded October 2000

3. Reason for Applying Syphilis epidemic in Marion County (Indianapolis) Indiana in 1999-2000 Wanted to identify common behavioral risk factors shared by STDs and HIV Focused on a limited geographic area

4. Pre-Application Approvals Program, Division, State Health Department and Local Health Department approval to match STD and HIV databases even though the databases were combined in a blinded fashion allow access to databases by contracted SAS programmer

5. Pre-Application Approvals Community Approval Stamp Out Syphilis Coalition (SOS) 40 City, State, County Community Group members and the affected neighborhood association HIV Prevention Community Planning (CPG) 35 individuals representing geographic, HIV service organizations, and risk behaviors reflecting Indiana HIV epidemic

6. Pre-Application Approvals Community Approval for the mutual beneficial outcome, not a search for recalcitrant behavior building confidence in our maintaining the confidentiality of the individual STD and HIV databases

7. Purpose of Project Promote integrated interpretation and use of STD and HIV surveillance data Identify STD and HIV behavioral risk profiles Share risk profiles with public health and community-based prevention and intervention programs Improve planning and evaluation of public health programs directed toward STD and HIV prevention Implement professional management of STD and HIV databases

8. Databases STD/MIS Chlamydia, Gonorrhea, Syphilis incidents in Indiana residents and DIS interview records of HIV 1999 through 2001 incidents 64,000+ records HARS (HIV/AIDS Reporting System) contains individual records all Indiana residents with HIV disease cumulative since 1982 11,000+ records

9. ISDH Program Areas Division of HIV/STD Epidemiologic Resource Center to activate a hiring contract for programmer Information Technology Services all 3 for concurrence for selection of programmer LAN administrator to allow access to databases

10. Pre-Integration Activities Determine required match criteria Identify common fields Assign common codes to each field Standardize HIV names and street addresses Clean STD database of duplicates and data entry errors and omissions

11. Key Construction A weighted combination of variables 18 keys developed Matches on keys were assigned points Match on every key worth 100 points

12. Variables Matched Name last, first, middle initial, alias, maiden name Single variable ‘address’ split into 10 standard variables number, direction, street, street type, post office box, city, state Date of birth day, month, and year

13. Variables Matched Telephone number area code, prefix, last four digits Sex Race County 5-digit zip code

14. Scoring Variable Comparison after Key Match Good quality score was valued at 78-82 Birth date data high score = 25 Good score without birth date match = 53-57 Our cutoff set at 65 point match so that a wider net would catch potential matches Individual review of low scoring matches would determine accuracy of the match

15. Data Observations The HIV surveillance records from 1982 through 2001 were compared to STD morbidity reports from the past three years: …Chlamydia matches 74 …Gonorrhea matches 132 …Syphilis (any stage) matches 47 (15 in 1999, 16 in 2000 and 16 in 2001)

16. When HIV data (1991-2001) is compared to STD (1999-2001: There were 254 matches for patients with dual infections ( HIV and another STD) in the past three years (1999-2001). The number of matches for early syphilis cases remained the same each year, while syphilis morbidity increased then decreased. 64% (161) of all matches occurred with patients residing in Marion County.

17. 2001: The data indicate that most dual infections involve patients who become infected with an STD after HIV diagnosis ( 80%) 24% Chlamydia acquired before HIV 25% Gonorrhea acquired before HIV 10% of Syphilis acquired before HIV

18. Marion County Matches 35 of 47 syphilis/HIV matches were in Marion County Risk factors were only collected in Marion County for syphilis

19. Marion County ResultsThrough August 31, 2001 18 did not identify a risk factor in STD/MIS 4 of these did not identify in HARS 23 did not identify a risk factor in HARS 4 of these did not identify in STD/MIS

20. Marion County ResultsThrough August 31, 2001 1 male had sex with a male in STD/MIS 7 males had sex with males in HARS implies we are not able to identify and provide appropriate prevention tools

21. Marion County ResultsThrough August 31, 2001 5 STD/MIS patients with more than 1 sex partner in last 90 days were identified in HARS as: 1 IDU 2 heterosexual contact with HIV infected person 2 no identified risk

22. Marion County ResultsThrough August 31, 2001 12 diagnosed with HIV after syphilis 6 white females in same zip codes and not in “hot zone” 4 black males and 6 of 7 females were white 10 concurrent diagnoses were related to non-injection drugs 6 MSM in HARS had no risk identified in STD/MIS 1 MSM in STD/MIS had no risk identified in HARS

23. Risk Factors of 6 White Femaleswith concurrent diagnoses >1 sex partner in last 90 days In county jail lock-up while infectious Used condoms with pickups only Sex with a ‘crack’ user Sex with a male “hot zone” linked

24. Recommendations Not include street address population moves too frequently Expand STD/MIS years of data to 1993 (morbidity only) Repeat match each year to examine effect of syphilis outbreak on HIV to identify subsequent infections with HIV Include all required fields in new database structures of STDMIS upgrades and HIV Surveillance software