Bridging the HIV treatment gap in Nigeria: examining community antiretroviral treatment models

INTRODUCTION: Significant gaps persist in providing HIV treatment to all who are in need. Restricting care delivery to healthcare facilities will continue to perpetuate this gap in limited resource settings. We assessed a large‐scale community‐based programme for effectiveness in identifying people living with HIV and linking them to antiretroviral treatment. METHODS: A retrospective secular trend study of 14 high burden local government areas of Nigeria was conducted in which two models of community antiretroviral treatment delivery were implemented: Model A (on‐site initiation) and Model B (immediate referral) clusters. Model A cluster offered services within communities, from HIV diagnosis to immediate antiretroviral therapy initiation and some follow‐up. Model B cluster offered services for HIV diagnosis up to baseline evaluation and provided referral for antiretroviral therapy initiation to nearest health facility providing HIV services. For controls, we selected and cluster‐matched 34 local government areas where community antiretroviral treatment delivery was not implemented. Outcomes of interest were: the number of people identified as HIV positive and the number of HIV‐positive individuals started on antiretroviral treatment; from June 2014 to May 2016. We used interrupted time‐series analysis to estimate outcome levels and trends across the pre‐and post‐intervention periods. RESULTS: Before community antiretrovial treatment introduction, Model A cluster identified, per 100,000 catchment population, 500 HIV‐positives (95% CI: 399.66 to 601.41) and initiated 216 HIV‐positives on antiretroviral treatment (95% CI: 152.72 to 280.10). Model B cluster identified 32 HIV‐positives (95% CI: 25.00 to 40.51) and initiated 8 HIV‐positives on antiretroviral treatment (95% CI: 5.54 to 10.33). After commART introduction, Model A cluster showed an immediate significant increase in 744 HIV‐positive persons (p = 0.00, 95% CI: 360.35 to 1127.77) and 560 HIV‐positives initiated on treatment (p = 0.00, 95% CI: 260.56 to 859.64). Model B cluster showed an immediate significant increase in 30 HIV‐positive persons identified (p = 0.01, 95% CI: 8.38 to 51.93) but not in the number of HIV‐positives initiated on treatment. Model B cluster showed increased month‐on‐month trends of both outcomes of interest (3.4, p = 0.02, 95% CI: 0.44 to 6.38). CONCLUSION: Both community‐models had similar population‐level effectiveness for rapidly identifying people living with HIV but differed in effectively transitioning them to treatment. Comprehensiveness, integration and attention to barriers to care are important in the design of community antiretroviral treatment delivery.