Browsing by Author "Bassett, Ingrid V"

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    Open Access
    Assessing rates and contextual predictors of 5-year mortality among HIV-infected and HIV-uninfected individuals following HIV testing in Durban, South Africa
    (2019-08-28) Bassett, Ingrid V; Xu, Ai; Giddy, Janet; Bogart, Laura M; Boulle, Andrew; Millham, Lucia; Losina, Elena; Parker, Robert A
    Abstract Background Little is known about contextual factors that predict long-term mortality following HIV testing in resource-limited settings. We evaluated the impact of contextual factors on 5-year mortality among HIV-infected and HIV-uninfected individuals in Durban, South Africa. Methods We used data from the Sizanani trial (NCT01188941) in which adults (≥18y) were enrolled prior to HIV testing at 4 outpatient sites. We ascertained vital status via the South African National Population Register. We used random survival forests to identify the most influential predictors of time to death and incorporated these into a Cox model that included age, gender, HIV status, CD4 count, healthcare usage, health facility type, mental health, and self-identified barriers to care (i.e., service delivery, financial, logistical, structural and perceived health). Results Among 4816 participants, 39% were HIV-infected. Median age was 31y and 49% were female. 380 of 2508 with survival information (15%) died during median follow-up of 5.8y. For both HIV-infected and HIV-uninfected participants, each additional barrier domain increased the HR of dying by 11% (HR 1.11, 95% CI 1.05–1.18). Every 10-point increase in mental health score decreased the HR by 7% (HR 0.93, 95% CI 0.89–0.97). The hazard ratio (HR) for death of HIV-infected versus HIV-uninfected varied by age: HR of 6.59 (95% CI: 4.79–9.06) at age 20 dropping to a HR of 1.13 (95% CI: 0.86–1.48) at age 60. Conclusions Independent of serostatus, more self-identified barrier domains and poorer mental health increased mortality risk. Additionally, the impact of HIV on mortality was most pronounced in younger persons. These factors may be used to identify high-risk individuals requiring intensive follow up, regardless of serostatus. Trial registration Clinical Trials.gov Identifier NCT01188941. Registered 26 August 2010.
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    The clinical and economic impact of point-of-care CD4 testing in Mozambique and other resource-limited settings: a cost-effectiveness analysis
    (Public Library of Science, 2014) Hyle, Emily P; Jani, Ilesh V; Lehe, Jonathan; Su, Amanda E; Wood, Robin; Quevedo, Jorge; Losina, Elena; Bassett, Ingrid V; Pei, Pamela P; Paltiel, A David
    Emily Hyle and colleagues conduct a cost-effectiveness analysis to estimate the clinical and economic impact of point-of-care CD4 testing compared to laboratory-based tests in Mozambique. Please see later in the article for the Editors' Summary
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    Linkage to HIV, TB and non-communicable disease care from a mobile testing unit in Cape Town, South Africa
    (Public Library of Science, 2013) Govindasamy, Darshini; Kranzer, Katharina; van Schaik, Nienke; Noubary, Farzad; Wood, Robin; Walensky, Rochelle P; Freedberg, Kenneth A; Bassett, Ingrid V; Bekker, Linda-Gail
    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.
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    Mobile HIV screening in Cape Town, South Africa: clinical impact, cost and cost-effectiveness
    (Public Library of Science, 2014) Bassett, Ingrid V; Govindasamy, Darshini; Erlwanger, Alison S; Hyle, Emily P; Kranzer, Katharina; van Schaik, Nienke; Noubary, Farzad; Paltiel, A David; Wood, Robin; Walensky, Rochelle P
    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.