Sarah L. Braunstein

Background: The epidemiologic utility of STARHS hinges not only on producing accurate estimates of HIV incidence, but also on identifying risk factors for recent HIV infection. Methods: As part of an HIV seroincidence study, 800 Rwandan female sex workers (FSW) were HIV tested, with those testing positive further tested by BED-CEIA (BED) and AxSYM Avidity Index (Ax-AI) assays. A sample of HIV-negative (N=397) FSW were followed prospectively for HIV seroconversion. We compared estimates of risk factors for: 1) prevalent HIV infection; 2) recently acquired HIV infection (RI) based on three different STARHS classifications (BED alone, Ax-AI alone, BED/Ax-AI combined); and 3) prospectively observed seroconversion. Results: There was mixed agreement in risk factors between methods. HSV-2 coinfection and recent STI treatment were associated with both prevalent HIV infection and all three measures of recent infection. A number of risk factors were associated only with prevalent infection, including widowhood, history of forced sex, regular alcohol consumption, prior imprisonment, and current breastfeeding. Number of sex partners in the last 3 months was associated with recent infection based on BED/Ax-AI combined, but not other STARHS-based recent infection outcomes or prevalent infection. Risk factor estimates for prospectively observed seroconversion differed in magnitude and direction from those for recent infection via STARHS. Conclusions: Differences in risk factor estimates by each method could reflect true differences in risk factors between the prevalent, recently, or newly infected populations, the effect of study interventions (among those followed prospectively), or assay misclassification. Similar investigations in other populations/settings are needed to further establish the epidemiologic utility of STARHS for identifying risk factors, in addition to incidence rate estimation.

The prevalence, incidence and persistence of human papillomavirus (HPV) types in sub-Saharan Africa are not well established. The objectives of the current study are to describe (predictors of) the epidemiology of HPV among high-risk women in Kigali, Rwanda.

To estimate HIV prevalence and risk factors in population-based samples of female sex workers (FSW) and female voluntary counseling and testing (VCT) clients in Rwanda. We conducted a cross-sectional survey of 800 FSW and 1,250 female VCT clients in Rwanda, which included interviewing and testing for HIV-1/2, HSV-2 and pregnancy, and BED-CEIA and Avidity Index (AI) to identify recent infections among HIV-infected women. Prevalence of HIV-1, HSV-2, and pregnancy were 24% (95% CI: 21.0–27.0), 59.8% (56.4–63.2), and 7.6% (5.8–9.5) among FSW, and 12.8% (10.9–14.6), 43.2% (40.4–46.0), and 11.4% (9.7–13.3) among VCT clients, respectively. Thirty-five percent of FSW and 25% of VCT clients had never been HIV tested. Per national guidelines, 33% of newly HIV-diagnosed FSW and 36% of VCT clients were already eligible for ART based on CD4<350 cells/µl. Condom use at last sex was higher among FSW (74%) than VCT clients (12%). In age and district of residence-adjusted models, HIV-1 seropositivity was associated with HSV-2 co-infection; recent treatment for sexually transmitted infection (STI); genital symptoms; forced sex; imprisonment; widowhood; and alcohol consumption. Eleven percent of FSW and 12% of VCT clients had recently acquired HIV-1 per BED-CEIA and AI. HSV-2 infection and recent STI treatment were associated with recent HIV infection in both groups, and being married and vaginal cleansing were associated with recent infection before last sex among VCT clients. This population-based survey reveals a high HIV prevalence and incidence among FSW and female VCT clients in Kigali, the scale of which is masked by the low general-population HIV prevalence in Rwanda. HIV/STI and family planning services should be strengthened.

Objective: To evaluate linkage-to-care, sexual behavior change, and psychosocial experiences among newly HIV-diagnosed female sex workers (FSWs) in Rwanda. Methods: FSWs (n = 800) with unknown serostatus were screened for HIV during 2007/2008. Women testing HIV positive (n = 192) were referred to care and asked to return for interviews and laboratory testing 12-36 months postdiagnosis. One hundred fourty-one women (73%) returned for the postdiagnosis visit. Results: Median CD4 count at diagnosis was 460 cells per microliter [interquartile range (IQR): 308-628], with 32% eligible for antiretroviral therapy (ART) per national CD4 criteria (median CD4: 235, IQR: 152-303). Postdiagnosis, 92% of women reported having disclosed their HIV status to a friend or relative, 85% reported having enrolled in HIV care (median 30 days after diagnosis, IQR: 7-360), including 89% among ART-eligible women. Among ART-eligible women in care, 87% had initiated ART, with a median follow-up CD4 count of 354 cells per microliter (IQR: 213-456). Women who did not initiate ART experienced a 6-month CD4 count change of −14 cells per microliter (IQR: −41 to 13). Three-quarters of women reported reduced sexual risk behavior postdiagnosis, with only 64% continuing to identify as FSWs. However, 53% reported past month condom use only “sometimes.” Conclusions: Timely linkage to care and ART uptake were high in this group of Rwandan FSWs. However, risky sexual behaviors remained common after enrollment in care. HIV-positive FSWs are an important and receptive group for targeted efforts to increase HIV diagnosis and linkage to care/treatment. Once in care, intensified and sustained HIV prevention education is necessary.

Measurement of human immunodeficiency virus (HIV) incidence among female sex workers in Rwanda is a key part of preparing for HIV prevention trials. HIV-negative, nonpregnant female sex workers (N = 397) were tested for HIV-1, sexually transmitted infections, and pregnancy quarterly for 12 months, and again at a 1-time year 2 visit. Additional women (N = 156) were tested for HIV at baseline and 6 to 12 months thereafter in a parallel study. A total of 19 participants seroconverted during follow-up, with 13 in the first 12 months. The 12-month HIV incidence rate (IR) was 3.5 (95% confidence interval: 1.6, 5.4) per 100 person-years (PY). There was a nonsignificant downward trend from 4.6/100 PY (1.6, 7.7) in the first 6 months to 2.2 (0.1, 4.4) in the second 6 months (IR ratio: 2.1 [95% confidence interval: 0.7, 7.8]). The year 2 IR was 2.1 (0.4, 3.7), and the HIV IR in the parallel study (in the absence of frequent study visits) was 3.3/100 PY (0, 7.0). HIV testing history, lifetime pregnancies, recent initiation of sex work, gonorrhea, syphilis, and change in reproductive intentions were associated with incident HIV infection. Incidence of pregnancy, herpes simplex virus-type 2, trichomoniasis, gonorrhea, chlamydia, and syphilis per 100 PY were as follows: 26.3 (21.9, 30.7), 8.7 (4.0, 13.4), 16.9 (12.7, 21.1), 12.1 (8.2, 15.9), 8.1 (5.1, 11.2), and 6.2 (3.7, 8.7). The HIV/sexually transmitted infections burden in this group was high. HIV IR was highest in the first 6 months of the cohort, and in the parallel study in which there were no risk-reduction procedures. HIV prevention and family planning interventions are needed.

To assess the performance of BED-CEIA (BED) and AxSYM Avidity Index (Ax-AI) assays in estimating HIV incidence among female sex workers (FSW) in Kigali, Rwanda. Eight hundred FSW of unknown HIV status were HIV tested; HIV-positive women had BED and Ax-AI testing at baseline and ≥12 months later to estimate assay false-recent rates (FRR). STARHS-based HIV incidence was estimated using the McWalter/Welte formula, and adjusted with locally derived FRR and CD4 results. HIV incidence and local assay window periods were estimated from a prospective cohort of FSW. At baseline, 190 HIV-positive women were BED and Ax-AI tested; 23 were classified as recent infection (RI). Assay FRR with 95% confidence intervals were: 3.6% (1.2–8.1) (BED); 10.6% (6.1–17.0) (Ax-AI); and 2.1% (0.4–6.1) (BED/Ax-AI combined). After FRR-adjustment, incidence estimates by BED, Ax-AI, and BED/Ax-AI were: 5.5/100 person-years (95% CI 2.2–8.7); 7.7 (3.2–12.3); and 4.4 (1.4–7.3). After CD4-adjustment, BED, Ax-AI, and BED/Ax-AI incidence estimates were: 5.6 (2.6–8.6); 9.7 (5.0–14.4); and 4.7 (2.0–7.5). HIV incidence rates in the first and second 6 months of the cohort were 4.6 (1.6–7.7) and 2.2 (0.1–4.4). Adjusted incidence estimates by BED/Ax-AI combined were similar to incidence in the first 6 months of the cohort. Furthermore, false-recent rate on the combined BED/Ax-AI algorithm was low and substantially lower than for either assay alone. Improved assay specificity with time since seroconversion suggests that specificity would be higher in population-based testing where more individuals have long-term infection.

HIV incidence estimation is increasingly being incorporated into HIV/AIDS surveillance activities in both resource-rich and developing countries. We conducted a systematic review to assess the availability of HIV incidence data from sub-Saharan Africa. We examined peer-reviewed articles, conference proceedings and technical reports published from 1987-2008. Incidence estimates were classified by country, year, population group, and estimation method (prospective study or the serologic testing algorithm for recent HIV seroconversion; STARHS). Our search yielded HIV incidence estimates for 15 of 44 sub-Saharan African countries, with 57 studies generating 264 unique estimates. Of these, 239 (91%) were obtained via prospective studies, and 25 (9%) via the STARHS method (24 using the BED-CEIA assay). Only five countries reported population-based estimates, and less than two-thirds of studies reported risk factor information. STARHS use increased over time, comprising 20% of estimates since 2006. However, studies that compared STARHS estimates with prospectively observed or modeled estimates often found substantial levels of disagreement, with STARHS often overestimating HIV incidence. Population-based HIV incidence estimates and risk factor information in sub-Saharan Africa remain scant but increasingly available. Regional STARHS data suggest a need for further validation prior to widespread use and incorporation into routine surveillance activities. In the meantime, prevalence and behavioral risk factor data remain important for HIV prevention planning.