Collins C Iwuji1, Joanna Orne-Gliemann2, Joseph Larmarange3, Eric Balestre2, Rodolphe Thiebaut2, Frank Tanser4, Nonhlanhla Okesola5, Thembisa Makowa5, Jaco Dreyer5, Kobus Herbst5, Nuala McGrath6, Till Bärnighausen7, Sylvie Boyer8, Tulio De Oliveira9, Claire Rekacewicz10, Brigitte Bazin10, Marie-Louise Newell11, Deenan Pillay12, François Dabis13. 1. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Research Department of Infection and Population Health, University College London, London, UK; Department of Global Health and Infection, Brighton and Sussex Medical School, University of Sussex, Brighton, UK. 2. University of Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France. 3. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Centre Population et Développement (UMR 196 Paris Descartes IRD), SageSud (ERL INSERM 1244), Institut de Recherche pour le Développement, Paris, France. 4. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; School of Nursing and Public Health, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa. 5. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa. 6. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Research Department of Epidemiology and Public Health, University College London, London, UK; Academic Unit of Primary Care and Population Sciences and Department of Social Statistics and Demography, University of Southampton, Southampton, UK. 7. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Department of Global Health and Population, Harvard School of Public Health, Harvard University, Boston, MA, USA; Institute of Public Health, Faculty of Medicine, Heidelberg University, Heidelberg, Germany. 8. Aix Marseille Univ, INSERM, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l'Information Médicale, Marseille, France. 9. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Nelson R Mandela School of Medicine, College of Health Sciences, University of KwaZulu-Natal, Durban, KwaZulu-Natal, South Africa. 10. Agence Nationale de Recherches sur le Sida et les hépatites virales (ANRS), Paris, France. 11. Human Development and Health, Global Health Research Institute, Faculty of Medicine, University of Southampton, Southampton, UK. 12. Africa Health Research Institute, Durban, KwaZulu-Natal, South Africa; Division of Infection and Immunity, University College London, London, UK. Electronic address: dpillay@ahri.org. 13. University of Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, UMR 1219, Bordeaux, France. Electronic address: francois.dabis@u-bordeaux.fr.
Abstract
BACKGROUND:Universal antiretroviral therapy (ART), as per the 2015 WHO recommendations, might reduce population HIV incidence. We investigated the effect of universal test and treat on HIV acquisition at population level in a high prevalence rural region of South Africa. METHODS: We did a phase 4, open-label, cluster randomised trial of 22 communities in rural KwaZulu-Natal, South Africa. We included individuals residing in the communities who were aged 16 years or older. The clusters were composed of aggregated local areas (neighbourhoods) that had been identified in a previous study in the Hlabisa subdistrict. The study statisticians randomly assigned clusters (1:1) with MapInfo Pro (version 11.0) to either the control or intervention communities, stratified on the basis of antenatal HIV prevalence. We offered residents repeated rapid HIV testing during home-based visits every 6 months for about 4 years in four clusters, 3 years in six clusters, and 2 years in 12 clusters (58 cluster-years) and referred HIV-positive participants to trial clinics for ART (fixed-dose combination of tenofovir, emtricitabine, and efavirenz) regardless of CD4 cell count (intervention) or according to national guidelines (initially ≤350 cells per μL and <500 cells per μL from January, 2015; control). Participants and investigators were not masked to treatment allocation. We used dried blood spots once every 6 months provided by participants who were HIV negative at baseline to estimate the primary outcome of HIV incidence with cluster-adjusted Poisson generalised estimated equations in the intention-to-treat population after 58 cluster-years of follow-up. This study is registered with ClinicalTrials.gov, number NCT01509508, and the South African National Clinical Trials Register, number DOH-27-0512-3974. FINDINGS:Between March 9, 2012, and June 30, 2016, we contacted 26 518 (93%) of 28 419 eligible individuals. Of 17 808 (67%) individuals with a first negative dried blood spot test, 14 223 (80%) hadsubsequent dried blood spot tests, of whom 503 seroconverted after follow-up of 22 891 person-years. Estimated HIV incidence was 2·11 per 100 person-years (95% CI 1·84-2·39) in the intervention group and 2·27 per 100 person-years (2·00-2·54) in the control group (adjusted hazard ratio 1·01, 95% CI 0·87-1·17; p=0·89). We documented one case of suicidal attempt in a woman following HIV seroconversion. 128 patients on ART had 189 life-threatening or grade 4 clinical events: 69 (4%) of 1652 in the control group and 59 (4%) of 1367 in the intervention group (p=0·83). INTERPRETATION: The absence of a lowering of HIV incidence in universal test and treat clusters most likely resulted from poor linkage to care. Policy change to HIV universal test and treat without innovation to improve health access is unlikely to reduce HIV incidence. FUNDING: ANRS, GiZ, and 3ie.
RCT Entities:
BACKGROUND: Universal antiretroviral therapy (ART), as per the 2015 WHO recommendations, might reduce population HIV incidence. We investigated the effect of universal test and treat on HIV acquisition at population level in a high prevalence rural region of South Africa. METHODS: We did a phase 4, open-label, cluster randomised trial of 22 communities in rural KwaZulu-Natal, South Africa. We included individuals residing in the communities who were aged 16 years or older. The clusters were composed of aggregated local areas (neighbourhoods) that had been identified in a previous study in the Hlabisa subdistrict. The study statisticians randomly assigned clusters (1:1) with MapInfo Pro (version 11.0) to either the control or intervention communities, stratified on the basis of antenatal HIV prevalence. We offered residents repeated rapid HIV testing during home-based visits every 6 months for about 4 years in four clusters, 3 years in six clusters, and 2 years in 12 clusters (58 cluster-years) and referred HIV-positive participants to trial clinics for ART (fixed-dose combination of tenofovir, emtricitabine, and efavirenz) regardless of CD4 cell count (intervention) or according to national guidelines (initially ≤350 cells per μL and <500 cells per μL from January, 2015; control). Participants and investigators were not masked to treatment allocation. We used dried blood spots once every 6 months provided by participants who were HIV negative at baseline to estimate the primary outcome of HIV incidence with cluster-adjusted Poisson generalised estimated equations in the intention-to-treat population after 58 cluster-years of follow-up. This study is registered with ClinicalTrials.gov, number NCT01509508, and the South African National Clinical Trials Register, number DOH-27-0512-3974. FINDINGS: Between March 9, 2012, and June 30, 2016, we contacted 26 518 (93%) of 28 419 eligible individuals. Of 17 808 (67%) individuals with a first negative dried blood spot test, 14 223 (80%) had subsequent dried blood spot tests, of whom 503 seroconverted after follow-up of 22 891 person-years. Estimated HIV incidence was 2·11 per 100 person-years (95% CI 1·84-2·39) in the intervention group and 2·27 per 100 person-years (2·00-2·54) in the control group (adjusted hazard ratio 1·01, 95% CI 0·87-1·17; p=0·89). We documented one case of suicidal attempt in a woman following HIV seroconversion. 128 patients on ART had 189 life-threatening or grade 4 clinical events: 69 (4%) of 1652 in the control group and 59 (4%) of 1367 in the intervention group (p=0·83). INTERPRETATION: The absence of a lowering of HIV incidence in universal test and treat clusters most likely resulted from poor linkage to care. Policy change to HIV universal test and treat without innovation to improve health access is unlikely to reduce HIV incidence. FUNDING: ANRS, GiZ, and 3ie.
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