Real-world data on HIV drug resistance (HIVDR) after transitioning to tenofovir disoproxil fumarate/lamivudine/dolutegravir (TLD) are limited. We assessed HIVDR rates and patterns in clients with virological failure (VF) after switching from an NNRTI-based regimen to TLD. A cross-sectional study was conducted in Gaza, Mozambique (August 2021–February 2022), including adults on first-line ART for ≥12 months who transitioned to TLD and had unsuppressed viral load (VL) ≥ 1000 copies/mL six months post-transition. After three adherence counseling sessions, participants with VF underwent genotyping for drug resistance mutations (DRMs) using the Stanford HIVdb Program. Of 717 participants (median age 39.2 years, 70.7% female), 217 (30.2%) had VF, 193 (88.9%) underwent genotyping, with 183 (94.8%) successfully genotyped. Intermediate–high dolutegravir (DTG) resistance was found in 19.6% (36/183). Unsuppressed VL before DTG transition was independently associated with VF (aOR: 2.14). Resistance patterns included 33.3% (12/36; 95% CI: 14.6–46.3) to all three TLD drugs, 55.6% (20/36; 95% CI: 39.3–71.9) to DTG and 3TC, and 11% (4/36; 95% CI: 0.8–21.3) to DTG only. Major drug resistance mutations to DTG included G118R (9.3%), R263K (6.6%), and Q148H/R/K (4.4%). This study highlights the need to consider virologic status before transitioning PLHIV to TLD and suggests that adherence counseling may not prevent resistance in those with unknown or prior VF.

With the increase in uptake of multi-month antiretroviral therapy dispensing (MMD) for children, little is known about consistency of MMD receipt over time and its association with virological outcomes. This analysis aims to assess the uptake of 3-month MMD among children, consistent receipt of MMD after uptake, and clinical outcomes following transition to MMD in 16 health facilities in Gaza and Inhambane Provinces. This is a secondary analysis involving children <15 years living with HIV with clinical visits during the period from September 2019 to August 2020. Of 4383 children, 82% ever received MMD (at least one pickup of a 3-month MMD supply) during the study period but only 40% received it consistently (defined as MMD at every visit during the study period). Consistent MMD was most common among older children and children without indications of clinical instability. Overall viral load (VL) coverage was 40% (733/1851). Consistent MMD was significantly associated with lower odds of having a VL (0.78, 95% CI: 0.64–0.95). In conclusion, while receipt of a multi-month supply was common particularly during the early days of the COVID-19 pandemic, only a minority of children received consistent MMD; however, there is a need to ensure children with fewer visits still receive timely VL monitoring.

The Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program delivers community- and clinic-based interventions to reduce HIV vulnerability among adolescent girls and young women (AGYW) aged 15–24 years. We conducted a retrospective programmatic financial cost analysis from the implementing partner perspective using financial and programmatic records from October 2022 to June 2023. We estimated the total costs and cost per AGYW enrolled (cost/AGYW) of DREAMS components in Gaza and Inhambane, Mozambique. A total of 19,477 AGYW were enrolled in Gaza and 3320 in Inhambane from October 2022 to June 2023. Clinic-based components cost US$189,047 in Gaza and US$67,826 in Inhambane, which amount to US$10 and US$20 per AGYW enrolled, respectively. Inhambane’s community component cost US$128,344, and US$39 per AGYW enrolled without Siyakha (an economic package that prepares AGYW to enter the job market). Among Siyakha recipients, the combined community and Siyakha cost was US$466 for 59 AGYW receiving the light package without internship and US$551 for 54 AGYW receiving the full package with internship. Human resources were the largest cost category across components, indicating that staffing requirements are a major determinant of DREAMS implementation costs. Human resources were the main cost driver in both components, highlighting the need to optimize staffing models.