Background
Despite reaching the UNAIDS 95-95-95 targets, many countries continue to face significant challenges with Interruption in Treatment (IIT). This analysis examines IIT rates from Fiscal years (FY) 2021 to 2024 across nine PEPFAR-supported countries—Botswana, Eswatini, Kenya, Lesotho, Malawi, Namibia, Rwanda, Zambia, and Zimbabwe—that have achieved or are nearing these targets. We explore IIT trends in the context of high treatment coverage (Tx_CURR) and viral load suppression (VLS) to identify persistent disparities and inform targeted interventions.
Methods
We conducted a longitudinal analysis of quarterly PEPFAR Monitoring, Evaluation, and Reporting (MER) data from FY2021 Q1 to FY2024 Q3 for nine aforementioned countries. We calculated percent IIT (defined as the proportion of the treatment cohort with no clinical contact or antiretroviral therapy pick-up > 28 days since the last expected encounter), Tx_CURR and VLS percentages for each quarter, stratified by sex. To assess disparities, we generated Lorenz curves to visualize the distribution of IIT across subnational regions within each country and collectively across all nine countries over time. Additionally, Gini coefficients were calculated to quantify the level of inequality in IIT distribution.
Results
The treatment cohort across nine countries increased from 5,252,596 individuals (64.2% female) in FY2021 Q2 to 5,932,928 (64.9% female) in FY2024 Q3, with VLS proportion remaining stable at 95.7%. During the study period, overall IIT decreased from 1.9% in FY2021 Q2 to 1.6% in FY2024 Q3. Throughout the duration analyzed, IIT was greater among men than women (2.02% vs. 1.72%, p<0.001). Lorenz curves indicated that IIT distribution was unequal but Gini coefficient decreased from 0.22 in Q2 FY2022 to 0.08 in Q3 FY2024 (Z score 5.04, p<0.001) (Figure), reflecting a substantial reduction in inequality.
Conclusions
While the overall volume of IIT and its distribution disparities decreased during the evaluated period, IIT remains a significant challenge in these nine countries. Our analysis using Lorenz curves and Gini coefficients underscores the importance of targeted interventions to maintain high continuity of treatment and prevent IIT. Specifically, tailored strategies are crucial in countries with significant inequalities in treatment continuity and among sub-populations with high IIT, such as men.