Calibration, validation and application of the HIV-1 BED Incidence Assay

1. Calibration, validation and application of the HIV-1 BED Incidence Assay Bharat S. Parekh, Ph.D. Centers for Disease Control and Prevention, Atlanta

2. Schematic of the BED-CEIA Plasma/serum (1/100) (1 h/37o C) Goat-anti-human-IgG Capture antibody BED-Biotin Peptide (gp41) (1 h/37o C) TMB Substrate (15 min/25o C) Strepavidin- Peroxidase (90 min/37o C)

3. Important features of gp41-Capture-EIA(BED-CEIA) • Competitive capture format of the EIA (HIV-IgG and non-HIV-IgG) • Indirectly measures increasing levels of HIV-IgG as a proportion of total IgG • Uses a multi-subtype, branched synthetic peptide (BED) from gp41-IDR to permit equivalent detection of divergent subtypes

4. Terminology • Calibration: Determining the “window of detection” for recent HIV infection by the BED assay in different subtypes • Validation: Assessing the accuracy of the BED-estimated HIV-1 incidence by comparing it to the observed incidence • Application: Applying the BED assay in cross-sectional populations for incidence surveillance, trend analysis and association with various risk factors

5. Initial Evaluation (Calibration) • Incident infections: N=139; n=622 • 22 BBI panels (subtype B) • 90 Thai Seroconverters – BMA • 18 Thai B • 72 Thai E • 37 from HIP or IDU study

6. Changes in OD-n after seroconversionUS B/Thai B/E FN TN TP FP 1.0/160 days

7. Window period in individual subtypes Subtype B Subtype E 1.0/170 days 1.0/150 days

8. Subsequent analysis • Misclassification in AIDS patients = ~4% • Lowering the cutoff to 0.8 further reduces misclassification (~2%) • Thai B window =~140 days • Thai E window =~120 days • Better predictive value

9. Further Calibration

10. Calibration in additional seroconverter specimens • Amsterdam cohort, N=25, n=100, subtype B • Kenya (prostitutes), N=34, n=97, subtypes A,D,c • Ethiopia (factory workers), N=21, n=115, subtype C • Zimbabwe (pregnant women) , N=158, n=585, subtype C

11. Amsterdam cohort seroconverterssubtype B 127 days

13. 181 days

14. Kenyan seroconverterssubtypes A/D/c

15. BED-CEIA “window of detection” at 0.800 cutoff Subtypes Country  Window (95% CI) AD  Kenya                  171 (150-199)  B      Amsterdam          127 (113-152) B’      Thailand              143 (118-170) C      Zimbabwe/Ethi     181 (165-198) E            Thailand              115 (106-125) OVERALL                153 (146-165)

16. Validation

17. Validation of the assay in cohorts with known incidence • Choose a population with conventional (follow-up) measure of incidence • Test positives collected during certain time-periods by the incidence assay • Calculate incidence (annualized per 100 persons per year) and compare to observed incidence

18. Summary of the BED assay validation in 3 prospective observational cohorts

19. Applications

20. Cross-Sectional Cohorts • BMA IDU screen specimens (Thailand), n=594 • BMA IDU VaxGen screen specimens, n=1554 • Uganda VCT, n=2023 • S. Africa – surveillance 2002, n=~1000 • Ethiopia Wonji & Surveillance, n=1600 • Cambodia Surveillance Specimens, n=~3600 • Emory Grady Hospital pregnant women, n=~300 • Rwanda, n=~600 • Thailand Surveillance = ~1000 • India, STD cohort in Chennai, n=~300

23. High versus Low Incidence • Seropositives found in pre-screened population are more likely to be recently infected>high incidence • Those who consent to enroll in the study have lower risk than those who do not • Risk-reduction counseling during the longitudinal follow-up can further lower the incidence >COHORT EFFECT

24. Cross-sectional studyBMA IDU Pre-screen • Specimens sorted by OD • Every 5th specimen assayed by Western blot

26. Cambodia Sentinel Surveillance • Positive specimens from 3 years: 1999, 2000 & 2002 (total N=3590) • 4 specific populations • ANC, CSW, IDSW and Police • Tested at UCLA (Fogarty Fellow from Cambodia)

27. HIV-1 incidence trends in specific risk groupsCambodia CSW IDSW Police

28. Regional Differences in IncidenceCSW - Cambodia Central West East

29. S. Africa : ANC Surveillance • 3109 pregnant women were tested for HIV-1 infection as part of ANC survey in Gauteng Province, 2002 • HIV-1 seropositive women = 936 (30.1%) • Age 12-49 (98.9%) • mean 25.9 • Other information available: • Education level • RPR

30. BED Incidence Testing • 106 (11.32%) of 936 women were found to be recently infected • For incidence rate calculation, window period used = 180 days • Overall incidence = 9.43 per 100 persons per year

31. Proportion of recent infection by Age

32. HIV-1 Prevalence and Incidence by Age

33. HIV-1 Prevalence and Incidence by Age

34. Association with Education PREVALENCE INCIDENCE

35. Association with RPR PREVALENCE INCIDENCE

36. Summary • The BED-CEIA has been calibrated in multiple HIV-1 subtypes. • It has relatively similar “windows of detection” with mean window of 153 days for detecting recent seroconversion • The assay has been validated in prospective cohorts and BED-estimated incidence values were similar to observed incidence • Applications in a number of cross-sectional populations are providing useful information about the incidence trends and its association with risk factors.

37. Acknowledgement International Collaborators • Thailand • Ethiopia • Zimbabwe • Kenya • Netherlands • S. Africa • Cambodia • Steve McDougal • Trudy Dobbs • Susan Kennedy • Chou Pau • Dale Hu • Tim Mastro • Nancy Young • Bob Byers/Tim Green • Julie Overbaugh • Dawit Wolday • Sapon Vonthanak • Adrian Puren • Roel Continho • Jean Humphrey