Caitlin F. GillIndiana University School of Medicine, Department of Public Health

Master of Public Health ProgramPBHL P704-Epidemiology-Final Concentration Project

December 8th, 2011

IRB Study Number: 1106006120

Background/Rationale

• Rates of infectious syphilis have increased in the USA during the past 10 years.

• A small group of syphilis cases, “core transmitters” are responsible for disease burden in a community.

• Determining the most effective case detection method to identify these cases can be invaluable to decreasing disease rates.

Kahn et al., 2006; Koumans et al., 2001; Bernstein et al., 2004

Study Aims

1. Determine the proportion of syphilis cases at high risk for transmission detected by each of the four case detection methods among the cases at Bell Flower Clinic reported from January 2008 through December 2010.

2. Assess differences in characteristics of those at high risk of transmission compared to the other early syphilis cases.

Study Design

• Cross-Sectional Study

• Dependent Variable: High-Risk of transmitting the disease.

• Independent Variables: Stage of infection, method of case detection, number of sex partners during the past 12 months, demographics and high-risk behaviors

Study Population

• Description: Primary, secondary or early-latent syphilis subjects diagnosed between January 1, 2008 through December 31st, 2010 at the Bell Flower Clinic located in Marion County, Indiana.

• Size: All subjects (n= 379) identified by one of the following methods of case detection.

Case Detection Methods

1. Disease Intervention Specialist (DIS): A staff member trained to treat, interview and follow up persons diagnosed with a sexually transmitted disease (STD).

2. Patient Referral: Patient referred by another STD infected person. This may be a named or unnamed partner. No health department involvement was needed for this referral.

3. Screening: An asymptomatic patient identified at initial evaluation conducted by a provider to determine whether a person is at risk for or has a STD.

4. Self-Referral: A patient who sought health services due to signs of a STD and was tested for the disease being reported.

Operational Definition of Variables• Syphilis: A sexually transmitted disease (STD) caused by the

bacterium Treponema pallidum.

• Primary Syphilis: Serum specimens with a nontreponemal rapid plasma reagin (RPR) fourfold rise in titer or a reactive FTA test.

• Secondary Syphilis: Presence of characteristic dermatologic lesions and a reactive nontreponemal RPR test (titer > 1:16).

• Early-latent Syphilis: After the primary and secondary phases have subsided, during the first year after infection, before any manifestations of tertiary syphilis have appeared.Centers for Disease Control and Prevention, 1997

• High-Risk Cases (n= 84):

Disease Stage Total Number of Reported Sex Partners

Primary syphilis ≥ 3 sex partners within last year.

Secondary syphilis ≥ 5 sex partners within last year.

Early-latent syphilis ≥ 11 sex partners within last year.

Data Source and Data Gathering Information

• Data extraction from Sexually Transmitted Disease Management System (STD*MIS) and the Statewide Information Management Surveillance System (SWIMSS) database.

• Included: Syphilis interview records and morbidity data from January 2008 through December 2010.

• Demographic elements- Sex, Age, Race/Ethnicity, etc.

• Case management data- Patient identification number, method of case detection, number of sex partners, sexual orientation, etc.

• Locally defined variables- History of incarceration in past 3 or 12 months, substance abuse, sex with an anonymous partner, sex while high and sex with an injection drug user (IDU).

Data Analysis

• Descriptive statistics were assessed for all variables.

• Chi-square statistics used to compare:

– Race/ethnicity and case characteristics.

–Method of case detection and case characteristics

–High and low risk and case characteristics

Table 1: Early Syphilis Cases by High and Low Risk Indianapolis2008-2010

High Risk (%) Low Risk (%)(N= 84) (N= 295) p-value

Race/Ethnicty p= 0.0579Black,non-Hispanic 40.5 52.5White, non-Hispanic 59.5 47.5

Sex p= 0.1475Female 7.1 12.9Male 92.9 87.1

Age (years) p= 0.7342<25 13.1 17.0

25-34 33.3 34.235-44 31.0 25.845+ 22.6 23.1

HIV Status p= 0.5611HIV + 55.6 51.7HIV - 44.4 48.3

Sexual Orientation p= 0.9365Heterosexual 27.7 28.2

MSM 72.3 71.8

Method of Case Detection p= 0.0162DIS 4.8 14.2

Patient Referral 9.5 13.6Screening 21.4 25.8

Self Referral 64.3 46.4

Table 1: Early Syphilis Cases by High and Low Risk Indianapolis2008-2010

High Risk (%) Low Risk (%)(N= 84) (N= 295) p-value

Drug Use p= 0.0069No 52.5 68.9Yes 47.5 31.1

Missing 4.8 9.5

County p= 0.6667Marion County 89.3 90.9

Surrounding Counties 10.7 9.2

Anonoymous Partner p<.0001No 16.7 52.5Yes 78.6 37.3

Sex while high p= 0.0128No 44.9 60.8Yes 55.1 39.2

Missing 5.9 15.7

Sex in exchange for drugs/money p<.0001No 81.0 95.1Yes 19.0 4.9

Sex with IDU p= 0.0434No 91.0 96.6Yes 9.0 3.5

Incarcerated p= 0.7269No 86.1 84.5Yes 13.9 15.5

Discussion

• Strengths: – Sample size (All subjects n= 379)– Examined many factors at one time

• Limitations:– Previously collected self-reported data– Can’t determine the time sequence between exposure and

outcome – Data entry errors/ missing data– Non-response of subjects for particular variables– Observation bias resulting in misclassification: overlap of primary

and secondary stage features of syphilis and reporting of false-negative serology in both primary and less commonly in secondary syphilis

Conclusion

• Case detection methods vary in their ability to identify high-risk transmission subjects.

• Screening and Self-referral were the two methods of case detection which identified the highest proportion of high-risk individuals.

• Continue to:

– screen high risk groups (MSM, incarcerated, commercial sex workers)

– quickly bring cases in for treatment

Future Research

• Conduct similar evaluations of syphilis prevention activities.

• Look at the individual characteristics of high-risk cases identified by each method of case detection and determine if there is a commonality among those subjects.

Acknowledgement

A special thank you to:

• Jutieh Lincoln, MPH (Marion County Public Health Department, Epidemiology)

• Janet N. Arno, M.D. (Marion County Public Health Department , Infectious Disease)

• Terrell W. Zollinger, Dr. P.H. (Indiana University Department of Public Health)

Questions?