Changes in rapid HIV treatment initiation after national "treat all" policy adoption in 6 sub-Saharan African countries: Regression discontinuity analysis

Abstract

Background: Most countries have formally adopted the World Health Organization's 2015 recommendation of universal HIV treatment ("treat all"). However, there are few rigorous assessments of the real-world impact of treat all policies on antiretroviral treatment (ART) uptake across different contexts.

Methods and findings: We used longitudinal data for 814,603 patients enrolling in HIV care between 1 January 2004 and 10 July 2018 in 6 countries participating in the global International epidemiology Databases to Evaluate AIDS (IeDEA) consortium: Burundi (N = 11,176), Kenya (N = 179,941), Malawi (N = 84,558), Rwanda (N = 17,396), Uganda (N = 96,286), and Zambia (N = 425,246). Using a quasi-experimental regression discontinuity design, we assessed the change in the proportion initiating ART within 30 days of enrollment in HIV care (rapid ART initiation) after country-level adoption of the treat all policy. A modified Poisson model was used to identify factors associated with failure to initiate ART rapidly under treat all. In each of the 6 countries, over 60% of included patients were female, and median age at enrollment ranged from 32 to 36 years. In all countries studied, national adoption of treat all was associated with large increases in rapid ART initiation. Significant increases in rapid ART initiation immediately after treat all policy adoption were observed in Rwanda, from 44.4% to 78.9% of patients (34.5 percentage points [pp], 95% CI 27.2 to 41.7; p < 0.001), Kenya (25.7 pp, 95% CI 21.8 to 29.5; p < 0.001), Burundi (17.7 pp, 95% CI 6.5 to 28.9; p = 0.002), and Malawi (12.5 pp, 95% CI 7.5 to 17.5; p < 0.001), while no immediate increase was observed in Zambia (0.4 pp, 95% CI -2.9 to 3.8; p = 0.804) and Uganda (-4.2 pp, 95% CI -9.0 to 0.7; p = 0.090). The rate of rapid ART initiation accelerated sharply following treat all policy adoption in Malawi, Uganda, and Zambia; slowed in Kenya; and did not change in Rwanda and Burundi. In post hoc analyses restricted to patients enrolling under treat all, young adults (16-24 years) and men were at increased risk of not rapidly initiating ART (compared to older patients and women, respectively). However, rapid ART initiation following enrollment increased for all groups as more time elapsed since treat all policy adoption. Study limitations include incomplete data on potential ART eligibility criteria, such as clinical status, pregnancy, and enrollment CD4 count, which precluded the assessment of rapid ART initiation specifically among patients known to be eligible for ART before treat all.

Conclusions: Our analysis indicates that adoption of treat all policies had a strong effect on increasing rates of rapid ART initiation, and that these increases followed different trajectories across the 6 countries. Young adults and men still require additional attention to further improve rapid ART initiation.

Fig 1. Rapid ART initiation (within 30 days of enrollment) across ART eligibility periods and enrollment CD4 counts (cells/μl).

Fig 2. Rapid ART initiation (within 30 days of enrollment) by ART eligibility period and country, 2007–2018.

Labels include effect sizes (percentage point [pp] change in the proportion of patients rapidly initiating ART) and 95% confidence intervals from the regression discontinuity analysis across the treat all adoption date threshold. Dotted lines on either side of the treat all date represent the width of the Imbens–Kalyanaraman bandwidth used in the regression discontinuity analysis. In order to comprehensively present observed trends, the graphs include the 30-day period preceding treat all adoption, which was excluded from regression discontinuity analysis (Table 3). The first 2 ART eligibility expansions (to CD4 ≤ 350 and ≤ 500 cells/μl) were not included in the regression discontinuity analysis, and data for the CD4 ≤ 350 cells/μl and CD4 ≤ 500 cells/μl eligibility periods are shown only for context. The plots include first degree local polynomial smooth curves intended for illustrative purposes and are distinct from the regression discontinuity models described in the Methods, from which effect estimates were derived. *Adjusted based on documented policy rollout delays (see Methods).