The "ART" of linkage: pre-treatment loss to care after HIV diagnosis at two PEPFAR sites in Durban, South Africa.
ABSTRACT Although loss to follow-up after antiretroviral therapy (ART) initiation is increasingly recognized, little is known about pre-treatment losses to care (PTLC) after an initial positive HIV test. Our objective was to determine PTLC in newly identified HIV-infected individuals in South Africa.
We assembled the South African Test, Identify and Link (STIAL) Cohort of persons presenting for HIV testing at two sites offering HIV and CD4 count testing and HIV care in Durban, South Africa. We defined PTLC as failure to have a CD4 count within 8 weeks of HIV diagnosis. We performed multivariate analysis to identify factors associated with PTLC. From November 2006 to May 2007, of 712 persons who underwent HIV testing and received their test result, 454 (64%) were HIV-positive. Of those, 206 (45%) had PTLC. Infected patients were significantly more likely to have PTLC if they lived > or = 10 kilometers from the testing center (RR = 1.37; 95% CI: 1.11-1.71), had a history of tuberculosis treatment (RR = 1.26; 95% CI: 1.00-1.58), or were referred for testing by a health care provider rather than self-referred (RR = 1.61; 95% CI: 1.22-2.13). Patients with one, two or three of these risks for PTLC were 1.88, 2.50 and 3.84 times more likely to have PTLC compared to those with no risk factors.
Nearly half of HIV-infected persons at two high prevalence sites in Durban, South Africa, failed to have CD4 counts following HIV diagnosis. These high rates of pre-treatment loss to care highlight the urgent need to improve rates of linkage to HIV care after an initial positive HIV test.
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ABSTRACT: Malaria, HIV, and tuberculosis (TB) collectively account for several million deaths each year, with all three ranking among the top ten killers in low-income countries. Despite being caused by very different organisms, malaria, HIV, and TB present a suite of challenges for mathematical modellers that are particularly pronounced in these infections, but represent general problems in infectious disease modelling, and highlight many of the challenges described throughout this issue. Here, we describe some of the unifying challenges that arise in modelling malaria, HIV, and TB, including variation in dynamics within the host, diversity in the pathogen, and heterogeneity in human contact networks and behaviour. Through the lens of these three pathogens, we provide specific examples of the other challenges in this issue and discuss their implications for informing public health efforts. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.Epidemics 02/2015; 350. DOI:10.1016/j.epidem.2015.02.002 · 2.38 Impact Factor
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ABSTRACT: There is limited research characterizing the HIV care continuum with population-based data in sub-Saharan Africa. The objectives of this study were to: 1) describe engagement in care among all known HIV-positive adults in one sub-county of western Kenya; and 2) determine the time to and predictors of linkage and engagement among adults newly diagnosed via home-based counseling and testing (HBCT). AMPATH (Academic Model Providing Access to Healthcare) has provided HIV care in western Kenya since 2001 and HBCT since 2007. Following a widespread HBCT program in Bunyala sub-county, electronic medical records (EMR) were reviewed to identify uptake of care among individuals with previously known (self-reported) infection and new (identified by HBCT) HIV diagnoses as of June 2014. Engagement in HIV care was defined as an initial encounter with an HIV care provider. Cox regression analysis was used to examine the predictors of engagement among those newly diagnosed. Of the 3,482 infected adults identified, 61% had previously known infections, among whom 84% (n = 1778/2122) had ever had at least one clinical encounter within AMPATH. While 73% were registered in the EMR, only 15% (n = 209/1360) of the newly diagnosed had seen a clinician over a median of 3·4 years. The median time to engagement among the newly diagnosed was 60 days (interquartile range: 10-411 days). Engagement in care was high among those who at the time of HBCT were already known HIV-positive, but few who were newly diagnosed in HBCT saw an HIV care provider. This research was supported by the President's Emergency Plan for AIDS Relief (PEPFAR) through USAID under the terms of Cooperative Agreement No. AID-623-A-12-0001. The HBCT program was supported by grants from Abbott Laboratories, the Purple ville Foundation, and the Global Business Coalition. Abbott Laboratories provided test kits and logistical support. Further support was provided by the National Institute of Mental Health (K01MH099966, PI: Genberg) and the Bill and Melinda Gates Foundation. The contents of this study are the sole responsibility of the authors and do not necessarily reflect the views of USAID, NIMH, BMGF, or the United States Government.The Lancet HIV 01/2015; 2(1):e20-e26. DOI:10.1016/S2352-3018(14)00034-4
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ABSTRACT: This paper reports on Kganya Motsha Adolescent Centre, an adolescent program specifically established to provide voluntary counseling and testing as well as management of HIV-positive young people in Soweto, South Africa. A retrospective cross-sectional analysis, using clinic records of young people accessing services from 2008 to 2012, was conducted. Of the 11,522 who tested, 7689 (67%) were females. The total number of HIV infections was 410, with an HIV prevalence of 3.6% (95% CI 3.2-3.9%). More females (332, 4% vs. 72, 2%; p < 0.0001) were HIV-infected than males. Of those testing HIV positive, 109 (26.5%) had a median CD4 cell count of 491 (IQR 345-686) cells/mm(3). Only 12/410 individuals (2.9%) were eligible for antiretroviral treatment and 10 (2.4%) of those successfully received treatment. The program observed that young people testing HIV positive would not return for follow up blood specimens or confirmatory results. Future programs should consider innovative ways of retaining adolescents in care to reduce potential HIV transmissions that could lead to deteriorating health.AIDS Care 01/2015; 27(6):1-6. DOI:10.1080/09540121.2014.993352 · 1.60 Impact Factor