Preliminary analysis of recent HIV infection in Kenya, KAIS 2007

1. Preliminary analysis of recent HIV infection in Kenya, KAIS 2007 Where are new infections occurring in Kenya? Tom Oluoch on behalf of the KAIS technical working group

2. Background Two distinct applications of serologic incidence assays Application 1: to estimate HIV incidence rates Application 2: to distinguish recent from long-standing infection Current incidence assays overestimate both recent infection and incidence rates due to misclassification of long-term infection as recent To minimize error: Application 1 (incidence estimation): Calibrate incidence estimate by incorporating correction factors based on expected misclassification rates into the mathematical formula for calculating incidence Application 2 (distinguishing recent infection): Predictive value can be improved using case-based exclusions to identify and exclude known long-term infections, based on data on ART, CD4 count, and HIV testing history Focus of this presentation is on Application 2 – the use of the BED assay and case-based exclusions to detect recent infections. Incidence rates will not be reported. 2

3. Methods • BED assay applied to frozen HIV antibody positive serum from the 2007 Kenya AIDS Indicator Survey (KAIS) • BED results linked to the KAIS questionnaire using unique study identification number • Case-based exclusions: Specimens that classified as BED recent and reported the following were re-classified as long-term infections and excluded from the incidence analysis • 1) Currently using ART • 2) Last HIV positive test that was >1 year ago, or • 3) CD4 cell counts < 500 • A CD4 cut-off of 500 was based on data from Uganda demonstrating a lower median baseline CD4 cell counts among HIV negatives (approximately 500 cells/mm3 using 90% ranges)

4. Methods • Weighted descriptive analysis conducted to characterize the distribution of recent infection by select demographic variables • Weighted multivariate analysis conducted to assess potential risk factors for recent infection • Outcome: Recent infection compared to HIV negative • Significant correlates represent risk factors for recent infection in the past 6 months

5. Number BED recent: 181 Number on ART: 21 Number CD4<500: 41 Number self-reported HIV infection> 1 year: 1 Excluded: 63 BED recent 11% of all HIV Ab+ The number of recent infection using case-based exclusions, KAIS 2007 Number HIV antibody + in KAIS: 1,073 Final number classified as recent infection: 118

6. Distribution of recent infection by gender and age group, KAIS 2007, N=118

7. Distribution of recent infection by residence, KAIS 2007, N=118 The vast majority of participants in the KAIS 2007 were from rural residences. Similarly, of all recent infections in KAIS, most (78%) were observed among rural participants compared to urban participants.

8. Distribution of recent infection among rural participants by gender and age, KAIS 2007 (N=86)

9. Distribution of recent infection by province and gender, KAIS 2007 (N=118)

10. Distribution of recent infection by marital status, KAIS 2007 (N=118) Serodiscordant couples in married/cohabitating relationships may be driving new infection in Kenya. Among all HIV-infected persons in KAIS that were married or cohabitating with another person, 44% had an HIV-uninfected partner

11. Distribution of recent infection by self-reported HIV testing status, KAIS 2007 (N=118)

12. Distribution of recent infection by circumcision status, Kenya and Nyanza Province, KAIS 2007 Kenya (N=118) Nyanza province (N=13)

13. Distribution of recent infection by HSV-2 status, KAIS 2007 (N=118)

14. Multivariate model: Risk factors for recent infection among females • *Comparison group is HIV negative persons. Model controlled for age, education, marital status, HSV-2, condom use with last sex partner, ever tested, ever used condom, number of partners in past 12 months, STD symptoms

15. Multivariate model: Risk factors for recent infection among males • *Comparison group is HIV negative persons. Model controlled for age, education, marital status, HSV-2, condom use with last sex partner, ever tested, ever used condom, number of partners in past 12 months, STD symptoms, GUD (males only), circumcision (males only)

16. Conclusion • The combination of BED results and case based exclusions using ART and CD4 data improved the predictive value for recent infection. • Analysis of recent infection in 2007 KAIS support a mixed epidemic in Kenya: • 1) New infections concentrated in Nyanza province fueled by lack of circumcism in males. • 2) New infections continue to be high in young people, especially women. HSV-2 appears to be a major risk factor. • 3) Recent infections were most notable in rural areas and higher among older rural men compared to older rural women. • 4) Most recent infections were found in married/cohabitating couples. Serodiscordancy and low condom use in these relationships are of major concern.

17. Conclusion • Data on recent infection in 2007 KAIS has provided critical information for prevention program planning in Kenya, including targeted programs and expansion of HIV testing. • Next step: application of dual incidence assay algorithm in KAIS (BED and Axsym Avidity Index assay). Results will be compared to case-based exclusion method.

18. Extra slides

19. Distribution of recent infection among married/cohabitating persons by gender and age group KAIS 2007 (N=86)