Noah Haber1, Frank Tanser2, Jacob Bor3, Kevindra Naidu4, Tinofa Mutevedzi5, Kobus Herbst5, Kholoud Porter6, Deenan Pillay7, Till Bärnighausen8. 1. Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Africa Health Research Institute, Somkhele, South Africa. Electronic address: nhaber@mail.harvard.edu. 2. Africa Health Research Institute, Somkhele, South Africa; School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa; Centre for the AIDS Programme of Research in South Africa-CAPRISA, University of KwaZulu-Natal, Congella, South Africa. 3. Africa Health Research Institute, Somkhele, South Africa; Department of Global Health, Boston University School of Public Health, Boston, MA, USA; Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa. 4. Africa Health Research Institute, Somkhele, South Africa; MatCH (Maternal Adolescent and Child Health Systems), School of Public Health, University of the Witwatersrand, South Africa. 5. Africa Health Research Institute, Somkhele, South Africa. 6. Africa Health Research Institute, Somkhele, South Africa; Research Department of Infection and Population Health, University College London, London, UK. 7. Africa Health Research Institute, Somkhele, South Africa; Division of Infection and Immunity, University College London, London, UK. 8. Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Africa Health Research Institute, Somkhele, South Africa; Institute of Public Health, Faculty of Medicine, University of Heidelberg, Heidelberg, Germany.
Abstract
BACKGROUND: Standard approaches to estimation of losses in the HIV cascade of care are typically cross-sectional and do not include the population stages before linkage to clinical care. We used indiviual-level longitudinal cascade data, transition by transition, including population stages, both to identify the health-system losses in the cascade and to show the differences in inference between standard methods and the longitudinal approach. METHODS: We used non-parametric survival analysis to estimate a longitudinal HIV care cascade for a large population of people with HIV residing in rural KwaZulu-Natal, South Africa. We linked data from a longitudinal population health surveillance (which is maintained by the Africa Health Research Institute) with patient records from the local public-sector HIV treatment programme (contained in an electronic clinical HIV treatment and care database, ARTemis). We followed up all people who had been newly detected as having HIV between Jan 1, 2006, and Dec 31, 2011, across six cascade stages: three population stages (first positive HIV test, HIV status knowledge, and linkage to care) and three clinical stages (eligibility for antiretroviral therapy [ART], initiation of ART, and therapeutic response). We compared our estimates to cross-sectional cascades in the same population. We estimated the cumulative incidence of reaching a particular cascade stage at a specific time with Kaplan-Meier survival analysis. FINDINGS: Our population consisted of 5205 individuals with HIV who were followed up for 24 031 person-years. We recorded 598 deaths. 4539 individuals gained knowledge of their positive HIV status, 2818 were linked to care, 2151 became eligible for ART, 1839 began ART, and 1456 had successful responses to therapy. We used Kaplan-Meier survival analysis to adjust for censorship due to the end of data collection, and found that 8 years after testing positive in the population health surveillance, 16% had died. Among living patients, 82% knew their HIV status, 45% were linked to care, 39% were eligible for ART, 35% initiated ART, and 33% had reached therapeutic response. Median times to transition for these cascade stages were 52 months, 52 months, 20 months, 3 months, and 9 months, respectively. Compared with the population stages in the cascade, the transitions across the clinical stages were fast. Over calendar time, rates of linkage to care have decreased and patients presenting for the first time for care were, on average, healthier. INTERPRETATION: HIV programmes should focus on linkage to care as the most important bottleneck in the cascade. Cascade estimation should be longitudinal rather than cross-sectional and start with the population stages preceding clinical care. FUNDING: Wellcome Trust, PEPFAR.
BACKGROUND: Standard approaches to estimation of losses in the HIV cascade of care are typically cross-sectional and do not include the population stages before linkage to clinical care. We used indiviual-level longitudinal cascade data, transition by transition, including population stages, both to identify the health-system losses in the cascade and to show the differences in inference between standard methods and the longitudinal approach. METHODS: We used non-parametric survival analysis to estimate a longitudinal HIV care cascade for a large population of people with HIV residing in rural KwaZulu-Natal, South Africa. We linked data from a longitudinal population health surveillance (which is maintained by the Africa Health Research Institute) with patient records from the local public-sector HIV treatment programme (contained in an electronic clinical HIV treatment and care database, ARTemis). We followed up all people who had been newly detected as having HIV between Jan 1, 2006, and Dec 31, 2011, across six cascade stages: three population stages (first positive HIV test, HIV status knowledge, and linkage to care) and three clinical stages (eligibility for antiretroviral therapy [ART], initiation of ART, and therapeutic response). We compared our estimates to cross-sectional cascades in the same population. We estimated the cumulative incidence of reaching a particular cascade stage at a specific time with Kaplan-Meier survival analysis. FINDINGS: Our population consisted of 5205 individuals with HIV who were followed up for 24 031 person-years. We recorded 598 deaths. 4539 individuals gained knowledge of their positive HIV status, 2818 were linked to care, 2151 became eligible for ART, 1839 began ART, and 1456 had successful responses to therapy. We used Kaplan-Meier survival analysis to adjust for censorship due to the end of data collection, and found that 8 years after testing positive in the population health surveillance, 16% had died. Among living patients, 82% knew their HIV status, 45% were linked to care, 39% were eligible for ART, 35% initiated ART, and 33% had reached therapeutic response. Median times to transition for these cascade stages were 52 months, 52 months, 20 months, 3 months, and 9 months, respectively. Compared with the population stages in the cascade, the transitions across the clinical stages were fast. Over calendar time, rates of linkage to care have decreased and patients presenting for the first time for care were, on average, healthier. INTERPRETATION: HIV programmes should focus on linkage to care as the most important bottleneck in the cascade. Cascade estimation should be longitudinal rather than cross-sectional and start with the population stages preceding clinical care. FUNDING: Wellcome Trust, PEPFAR.
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