Person:

Bassett, Ingrid

Objective: To estimate the prevalence of drug-resistant tuberculosis (TB) and describe the resistance patterns in patients commencing antiretroviral therapy (ART) in an HIV clinic in Durban, South Africa. Design Cross-sectional cohort study. Methods Consecutive HIV-infected adults (≥18y/o) initiating HIV care were enrolled from May 2007–May 2008, regardless of signs or symptoms of active TB. Prior TB history and current TB treatment status were self-reported. Subjects expectorated sputum for culture (MGIT liquid and 7H11 solid medium). Positive cultures were tested for susceptibility to first- and second-line anti-tuberculous drugs. The prevalence of drug-resistant TB, stratified by prior TB history and current TB treatment status, was assessed. Results: 1,035 subjects had complete culture results. Median CD4 count was 92/µl (IQR 42–150/µl). 267 subjects (26%) reported a prior history of TB and 210 (20%) were receiving TB treatment at enrollment; 191 (18%) subjects had positive sputum cultures, among whom the estimated prevalence of resistance to any antituberculous drug was 7.4% (95% CI 4.0–12.4). Among those with prior TB, the prevalence of resistance was 15.4% (95% CI 5.9–30.5) compared to 5.2% (95% CI 2.1–8.9) among those with no prior TB. 5.1% (95% CI 2.4–9.5) had rifampin or rifampin plus INH resistance. Conclusions: The prevalence of TB resistance to at least one drug was 7.4% among adults with positive TB cultures initiating ART in Durban, South Africa, with 5.1% having rifampin or rifampin plus INH resistance. Improved tools for diagnosing TB and drug resistance are urgently needed in areas of high HIV/TB prevalence.

Objectives: Although youth (12–24 years) in Sub-Saharan Africa have a high HIV risk, many have poor access to HIV testing services and are unaware of their status. Our objective was to evaluate the proportion of adolescents (12–17 years) and young adults (18–24 years) who underwent HIV testing and the prevalence among those tested in an urban adult outpatient clinic with a routine HIV testing program in Durban, South Africa. Design: We conducted a retrospective cross-sectional analysis of adolescent and young adult outpatient records between February 2008 and December 2009. Methods: We determined the number of unique outpatient visitors, HIV tests, and positive rapid tests among those tested. Results: During the study period, 956 adolescents registered in the outpatient clinic, of which 527 (55%) were female. Among adolescents, 260/527 (49%, 95% CI 45–54%) females underwent HIV testing compared to 129/429 (30%, 95% CI 26–35%) males (p<0.01). The HIV prevalence among the 389 (41%, 95% CI 38–44%) adolescents who underwent testing was 16% (95% CI 13–20%) and did not vary by gender (p = 0.99). During this period, there were 2,351 young adult registrations, and of these 1,492 (63%) were female. The proportion consenting for HIV testing was similar among females 980/1,492 (66%, 95% CI 63–68%) and males 543/859 (63%, 95% CI 60–66%, p = 0.25). Among the 1,523 (65%, 95% CI 63–67%) young adults who underwent testing, the HIV prevalence was 22% (95% CI 19–24%) in females versus 14% in males (95% CI 11–17%, p<0.01). Conclusions: Although the HIV prevalence is high among youth participating in an adult outpatient clinic routine HIV program, the uptake of testing is low, especially among 12–17 year old males. There is an urgent need to offer targeted, age-appropriate routine HIV testing to youth presenting to outpatient clinics in epidemic settings.

Background: Routine screening for HIV infection leads to early detection and treatment. We examined patient characteristics associated with repeated screening in a high prevalence country. Methods: We analyzed data from a cohort of 5,229 adults presenting for rapid HIV testing in the outpatient departments of 2 South African hospitals from November 2006 to August 2010. Patients were eligible if they were ≥18 years, reported no previous diagnosis with HIV infection, and not pregnant. Before testing, participants completed a questionnaire including gender, age, HIV testing history, health status, and knowledge about HIV and acquaintances with HIV. Enrollment HIV test results and CD4 counts were abstracted from the medical record. We present prevalence of HIV infection and median CD4 counts by HIV testing history (first-time vs. repeat). We estimated adjusted relative risks (ARR’s) for repeat testing by demographics, health status, and knowledge of HIV and others with HIV in a generalized linear model. Results: Of 4,877 participants with HIV test results available, 26% (N = 1258) were repeat testers. Repeat testers were less likely than first-time testers to be HIV-infected (34% vs. 54%, p<0.001). Median CD4 count was higher among repeat than first-time testers (201/uL vs. 147/uL, p<0.001). Among those HIV negative at enrollment (N = 2,499), repeat testing was more common among those with family or friends living with HIV (ARR 1.50, 95% CI: 1.33–1.68), women (ARR: 1.24, 95% CI: 1.11–1.40), and those self-reporting very good health (ARR: 1.28, 95% CI: 1.12–1.45). Conclusions: In this high prevalence setting, repeat testing was common among those undergoing HIV screening, and was associated with female sex, lower prevalence of HIV infection, and higher CD4 counts at diagnosis.

Background: HIV counseling and testing may serve as an entry point for non-communicable disease screening. Objectives: To determine the yield of newly-diagnosed HIV, tuberculosis (TB) symptoms, diabetes and hypertension, and to assess CD4 count testing, linkage to care as well as correlates of linkage and barriers to care from a mobile testing unit. Methods: A mobile unit provided screening for HIV, TB symptoms, diabetes and hypertension in Cape Town, South Africa between March 2010 and September 2011. The yield of newly-diagnosed cases of these conditions was measured and clients were followed-up between January and November 2011 to assess linkage. Linkage to care was defined as accessing care within one, three or six months post-HIV diagnosis (dependent on CD4 count) and one month post-diagnosis for other conditions. Clinical and socio-demographic correlates of linkage to care were evaluated using Poisson regression and barriers to care were determined. Results: Of 9,806 clients screened, the yield of new diagnoses was: HIV (5.5%), TB suspects (10.1%), diabetes (0.8%) and hypertension (58.1%). Linkage to care for HIV-infected clients, TB suspects, diabetics and hypertensives was: 51.3%, 56.7%, 74.1% and 50.0%. Only disclosure of HIV-positive status to family members or partners (RR=2.6, 95% CI: 1.04-6.3, p=0.04) was independently associated with linkage to HIV care. The main barrier to care reported by all groups was lack of time to access a clinic. Conclusion: Screening for HIV, TB symptoms and hypertension at mobile units in South Africa has a high yield but inadequate linkage. After-hours and weekend clinics may overcome a major barrier to accessing care.

Background: Despite increases in HIV testing, only a fraction of people newly diagnosed with HIV infection enter the care system and initiate antiretroviral therapy (ART) in South Africa. We report on the design and initial enrollment of a randomized trial of a health system navigator intervention to improve linkage to HIV care and TB treatment completion in Durban, South Africa. Methods/Design We employed a multi-site randomized controlled trial design. Patients at 4 outpatient sites were enrolled prior to HIV testing. For all HIV-infected participants, routine TB screening with sputum for mycobacterial smear and culture were collected. HIV-infected participants were randomized to receive the health system navigator intervention or usual care. Participants in the navigator arm underwent a baseline interview using a strengths-based case management approach to assist in identifying barriers to entering care and devising solutions to best cope with perceived barriers. Over 4 months, participants in the navigator arm received scheduled phone and text messages. The primary outcome of the study is linkage and retention in care, assessed 9 months after enrollment. For ART-eligible participants without TB, the primary outcome is 3 months on ART as documented in the medical record; participants co-infected with TB are also eligible to meet the primary outcome of completion of 6 months of TB treatment, as documented by the TB clinic. Secondary outcomes include mortality, receipt of CD4 count and TB test results, and repeat CD4 counts for those not ART-eligible at baseline. We hypothesize that a health system navigator can help identify and positively affect modifiable patient factors, including self-efficacy and social support, that in turn can improve linkage to and retention in HIV and TB care. Discussion We are currently evaluating the clinical impact of a novel health system navigator intervention to promote entry to and retention in HIV and TB care for people newly diagnosed with HIV. The details of this study protocol will inform clinicians, investigators, and policy makers of strategies to best support HIV-infected patients in resource-limited settings. Trial registration Clinicaltrials.gov. unique identifier: NCT01188941.

Background: Point-of-care CD4 tests at HIV diagnosis could improve linkage to care in resource-limited settings. Our objective is to evaluate the clinical and economic impact of point-of-care CD4 tests compared to laboratory-based tests in Mozambique. Methods and Findings: We use a validated model of HIV testing, linkage, and treatment (CEPAC-International) to examine two strategies of immunological staging in Mozambique: (1) laboratory-based CD4 testing (LAB-CD4) and (2) point-of-care CD4 testing (POC-CD4). Model outcomes include 5-y survival, life expectancy, lifetime costs, and incremental cost-effectiveness ratios (ICERs). Input parameters include linkage to care (LAB-CD4, 34%; POC-CD4, 61%), probability of correctly detecting antiretroviral therapy (ART) eligibility (sensitivity: LAB-CD4, 100%; POC-CD4, 90%) or ART ineligibility (specificity: LAB-CD4, 100%; POC-CD4, 85%), and test cost (LAB-CD4, US$10; POC-CD4, US$24). In sensitivity analyses, we vary POC-CD4-specific parameters, as well as cohort and setting parameters to reflect a range of scenarios in sub-Saharan Africa. We consider ICERs less than three times the per capita gross domestic product in Mozambique (US$570) to be cost-effective, and ICERs less than one times the per capita gross domestic product in Mozambique to be very cost-effective. Projected 5-y survival in HIV-infected persons with LAB-CD4 is 60.9% (95% CI, 60.9%–61.0%), increasing to 65.0% (95% CI, 64.9%–65.1%) with POC-CD4. Discounted life expectancy and per person lifetime costs with LAB-CD4 are 9.6 y (95% CI, 9.6–9.6 y) and US$2,440 (95% CI, US$2,440–US$2,450) and increase with POC-CD4 to 10.3 y (95% CI, 10.3–10.3 y) and US$2,800 (95% CI, US$2,790–US$2,800); the ICER of POC-CD4 compared to LAB-CD4 is US$500/year of life saved (YLS) (95% CI, US$480–US$520/YLS). POC-CD4 improves clinical outcomes and remains near the very cost-effective threshold in sensitivity analyses, even if point-of-care CD4 tests have lower sensitivity/specificity and higher cost than published values. In other resource-limited settings with fewer opportunities to access care, POC-CD4 has a greater impact on clinical outcomes and remains cost-effective compared to LAB-CD4. Limitations of the analysis include the uncertainty around input parameters, which is examined in sensitivity analyses. The potential added benefits due to decreased transmission are excluded; their inclusion would likely further increase the value of POC-CD4 compared to LAB-CD4. Conclusions: POC-CD4 at the time of HIV diagnosis could improve survival and be cost-effective compared to LAB-CD4 in Mozambique, if it improves linkage to care. POC-CD4 could have the greatest impact on mortality in settings where resources for HIV testing and linkage are most limited. Please see later in the article for the Editors' Summary

Background: After observing persistently low CD4 counts at initial HIV diagnosis in South Africa, we sought to determine risk factors for late-stage HIV disease presentation among adults. Methods: We surveyed adults prior to HIV testing at four outpatient clinics in Durban from August 2010 to November 2011. All HIV-infected adults were offered CD4 testing, and late-stage HIV disease was defined as a CD4 count (<100 cells/mm^{3}). We used multivariate regression models to determine the effects of sex, emotional health, social support, distance from clinic, employment, perceived barriers to receiving healthcare, and foregoing healthcare to use money for food, clothing, or housing (“competing needs to healthcare”) on presentation with late-stage HIV disease. Results: Among 3,669 adults screened, 830 were enrolled, newly-diagnosed with HIV and obtained a CD4 result. Among those, 279 (33.6%) presented with late-stage HIV disease. In multivariate analyses, participants who lived ≥5 kilometers from the test site [adjusted odds ratio (AOR) 2.8, 95% CI 1.7–4.7], reported competing needs to healthcare (AOR 1.7, 95% CI 1.2–2.4), were male (AOR 1.7, 95% CI 1.2–2.3), worked outside the home (AOR 1.5, 95% CI 1.1–2.1), perceived health service delivery barriers (AOR 1.5, 95% CI 1.1–2.1), and/or had poor emotional health (AOR 1.4, 95% CI 1.0–1.9) had higher odds of late-stage HIV disease presentation. Conclusions: Independent risk factors for late-stage HIV disease presentation were from diverse domains, including geographic, economic, demographic, social, and psychosocial. These findings can inform various interventions, such as mobile testing or financial assistance, to reduce the risk of presentation with late-stage HIV disease.

Background: Resource-limited countries increasingly depend on quality indicators to improve outcomes within HIV treatment programs, but indicators of program performance suitable for use at the local program level remain underdeveloped. Methods: Using the existing literature as a guide, we applied standard quality improvement (QI) concepts to the continuum of HIV care from HIV diagnosis, to enrollment and retention in care, and highlighted critical service delivery process steps to identify opportunities for performance indicator development. We then identified existing indicators to measure program performance, citing examples used by pivotal donor agencies, and assessed their feasibility for use in surveying local program performance. Clinical delivery steps without existing performance measures were identified as opportunities for measure development. Using National Quality Forum (NQF) criteria as a guide, we developed measurement concepts suitable for use at the local program level that address existing gaps in program performance assessment. Results: This analysis of the HIV continuum of care identified seven critical process steps providing numerous opportunities for performance measurement. Analysis of care delivery process steps and the application of NQF criteria identified 24 new measure concepts that are potentially useful for improving operational performance in HIV care at the local level. Conclusion: An evidence-based set of program-level quality indicators is critical for the improvement of HIV care in resource-limited settings. These performance indicators should be utilized as treatment programs continue to grow.

Background: Mobile HIV screening may facilitate early HIV diagnosis. Our objective was to examine the cost-effectiveness of adding a mobile screening unit to current medical facility-based HIV testing in Cape Town, South Africa. Methods and Findings: We used the Cost Effectiveness of Preventing AIDS Complications International (CEPAC-I) computer simulation model to evaluate two HIV screening strategies in Cape Town: 1) medical facility-based testing (the current standard of care) and 2) addition of a mobile HIV-testing unit intervention in the same community. Baseline input parameters were derived from a Cape Town-based mobile unit that tested 18,870 individuals over 2 years: prevalence of previously undiagnosed HIV (6.6%), mean CD4 count at diagnosis (males 423/µL, females 516/µL), CD4 count-dependent linkage to care rates (males 31%–58%, females 49%–58%), mobile unit intervention cost (includes acquisition, operation and HIV test costs, $29.30 per negative result and $31.30 per positive result). We conducted extensive sensitivity analyses to evaluate input uncertainty. Model outcomes included site of HIV diagnosis, life expectancy, medical costs, and the incremental cost-effectiveness ratio (ICER) of the intervention compared to medical facility-based testing. We considered the intervention to be “very cost-effective” when the ICER was less than South Africa's annual per capita Gross Domestic Product (GDP) ($8,200 in 2012). We projected that, with medical facility-based testing, the discounted (undiscounted) HIV-infected population life expectancy was 132.2 (197.7) months; this increased to 140.7 (211.7) months with the addition of the mobile unit. The ICER for the mobile unit was $2,400/year of life saved (YLS). Results were most sensitive to the previously undiagnosed HIV prevalence, linkage to care rates, and frequency of HIV testing at medical facilities. Conclusion: The addition of mobile HIV screening to current testing programs can improve survival and be very cost-effective in South Africa and other resource-limited settings, and should be a priority.

Background: The instability faced by refugees may place them at increased risk of exposure to HIV infection. Nakivale Refugee Settlement in southwestern Uganda hosts 68,000 refugees from 11 countries, many with high HIV prevalence. We implemented an HIV screening program in Nakivale and examined factors associated with new HIV diagnosis. Methods: From March 2013-November 2014, we offered free HIV screening to all clients in the Nakivale Health Center while they waited for their outpatient clinic visit. Clients included refugees and Ugandan nationals accessing services in the settlement. Prior to receiving the HIV test result, participants were surveyed to obtain demographic information including gender, marital status, travel time to reach clinic, refugee status, and history of prior HIV testing. We compared variables for HIV-infected and non-infected clients using Pearson’s chi-square test, and used multivariable binomial regression models to identify predictors of HIV infection. Results: During the HIV screening intervention period, 330 (4%) of 7766 individuals tested were identified as HIV-infected. Refugees were one quarter as likely as Ugandan nationals to be HIV-infected (aRR 0.27 [0.21, 0.34], p < 0.0001). Additionally, being female (aRR 1.43 [1.14, 1.80], p = 0.002) and traveling more than 1 h to the clinic (aRR 1.39 [1.11, 1.74], p = 0.003) increased the likelihood of being HIV-infected. Compared to individuals who were married or in a stable relationship, being divorced/separated/widowed increased the risk of being HIV-infected (aRR 2.41 [1.88, 3.08], p < 0.0001), while being single reduced the risk (aRR 0.60 [0.41, 0.86], p < 0.0001). Having been previously tested for HIV (aRR 0.59 [0.47, 0.74], p < 0.0001) also lowered the likelihood of being HIV-infected. Conclusions: In an HIV screening program in a refugee settlement in Uganda, Ugandan nationals are at higher risk of having HIV than refugees. The high HIV prevalence among clients seeking outpatient care, including Ugandan nationals and refugees, warrants enhanced HIV screening services in Nakivale and in the surrounding region. Findings from this research may be relevant for other refugee settlements in Sub-Saharan Africa hosting populations with similar demographics, including the 9 other refugee settlements in Uganda.