Background: The number of people living with HIV (PLHIV) in need of treatment monitoring in low-and-middle-income countries is rapidly expanding, straining existing laboratory capacity. Point-of-care viral load (POC VL) testing can alleviate the burden on centralized laboratories and enable faster delivery of results, improving clinical outcomes. However, implementation costs are uncertain and will depend on clinic testing volume. We sought to estimate the costs of decentralized POC VL testing compared to centralized laboratory testing for adults and children receiving HIV care in Kenya. Methods: We conducted microcosting to estimate the per-patient costs of POC VL testing compared to known costs of centralized laboratory testing. We completed time-and-motion observations and stakeholder interviews to assess personnel structures, staff time, equipment costs, and laboratory processes associated with POC VL administration. Capital costs were estimated using a 5 year lifespan and a 3% annual discount rate. Results: We estimated that POC VL testing cost USD $24.25 per test, assuming a clinic is conducting 100 VL tests per month. Test cartridge and laboratory equipment costs accounted for most of the cost (62% and 28%, respectively). Costs varied by number of VL tests conducted at the clinic, ranging from $54.93 to $18.12 per test assuming 20 to 500 VL tests per month, respectively. A VL test processed at a centralized laboratory was estimated to cost USD $25.65. Conclusion: POC VL testing for HIV treatment monitoring can be feasibly implemented in clinics within Kenya and costs declined with higher testing volumes. Our cost estimates are useful to policymakers in planning resource allocation and can inform cost-effectiveness analyses evaluating POC VL testing.

As many as 40% of the 1 million children living with HIV (CLHIV) receiving antiretroviral treatment (ART) in resource limited settings have not achieved viral suppression (VS). Kenya has a large burden of pediatric HIV with nearly 140,000 CLHIV. Feasible, scalable, and cost-effective approaches to ensure VS in CLHIV are urgently needed. The goal of this study is to determine the feasibility and impact of point-of-care (POC) viral load (VL) and targeted drug resistance mutation (DRM) testing to improve VS in children on ART in Kenya. We are conducting a randomized controlled study to evaluate the use of POC VL and targeted DRM testing among 704 children aged 1–14 years on ART at health facilities in western Kenya. Children are randomized 1:1 to intervention (higher frequency POC VL and targeted DRM testing) vs. control (standard-of-care) arms and followed for 12 months. Our primary outcome is VS (VL < 1000 copies/mL) 12 months after enrollment by study arm. Secondary outcomes include time to VS and the impact of targeted DRM testing on VS. In addition, key informant interviews with patients and providers will generate an understanding of how the POC VL intervention functions. Finally, we will model the cost-effectiveness of POC VL combined with targeted DRM testing. This study will provide critical information on the impact of POC VL and DRM testing on VS among CLHIV on ART in a resource-limited setting and directly address the need to find approaches that maximize VS among children on ART. NCT03820323.

Increasing HIV drug resistance (DR) among children with HIV (CHIV) on antiretroviral treatment (ART) is concerning. CHIV ages 1–14 years enrolled from March 2019 to December 2020 from five facilities in Kisumu County, Kenya, were included. Children were randomized 1:1 to control (standard-of-care) or intervention (point-of-care viral load (POC VL) testing every three months with targeted genotypic drug resistance testing (DRT) for virologic failure (VF) (≥1000 copies/mL)). A multidisciplinary committee reviewed CHIV with DRT results and offered treatment recommendations. We describe DR mutations and present logistic regression models to identify factors associated with clinically significant DR. We enrolled 704 children in the study; the median age was 9 years (interquartile range (IQR) 7, 12), 344 (49%) were female, and the median time on ART was 5 years (IQR 3, 8). During the study period, 106 (15%) children had DRT results (84 intervention and 22 control). DRT detected mutations associated with DR in all participants tested, with 93 (88%) having major mutations, including 51 (54%) with dual-class resistance. A history of VF in the prior 2 years (adjusted odds ratio (aOR) 11.1; 95% confidence interval (CI) 6.3, 20.0) and less than 2 years on ART at enrollment (aOR 2.2; 95% CI 1.1, 4.4) were associated with increased odds of major DR. DR is highly prevalent among CHIV on ART with VF in Kenya. Factors associated with drug resistance may be used to determine which children should be prioritized for DRT.

Increasing HIV drug resistance (DR) among children with HIV (CHIV) on antiretroviral treatment (ART) is concerning. CHIV ages 1-14 years enrolled March 2019 to December 2020 from five facilities in Kisumu County, Kenya were included. Children were randomized 1:1 to control (standard-of-care) or intervention (point-of-care viral load (POC VL) testing every three months with targeted genotypic drug resistance testing (DRT) for VF (> 1000 copies/ml)). A multidisciplinary committee reviewed CHIV with DRT results and offered treatment recommendations. We describe DR mutations and present logistic regression models to identify factors associated with clinically significant DR. We enrolled 704 children in the study; median age was 9 years (interquartile range (IQR) 7,12), 344 (49%) were female and median time on ART was 5 years (IQR 3, 8). During the study period, 106 (15%) children had DRT results (84 intervention and 22 control). DRT detected mutations associate with DR in all participants tested, with 93 (88%) having major mutations, including 51 (54%) with dual class resistance. A history of VF in prior 2 years (adjusted odds ratio (aOR) 11.1; 95% confidence interval (CI) 6.3, 20.0) and less than 2 years on ART at enrollment (aOR 2.2; 95% CI 1.1, 4.4) were associated with increased odds of major DR. DR is highly prevalent among CHIV on ART with VF in Kenya. Factors associated with drug resistance may be used to determine which children should be prioritized for DRT.

Background: There is insufficient data to inform the management of dolutegravir failure, with the WHO and various countries adopting different approaches, underscoring the need for an evidence-based management approach. Methods: The Ndovu study is a large multi-country cohort, with a nested randomised controlled trial (RCT), enrolling 6,600 people living with HIV (PLWH) with viral load (VL) of ≥1000 copies/ml after at least 6 months of dolutegravir. Participants aged ≥ 1 year, including pregnant women, will be followed up for 12 months with enhanced adherence counselling (EAC) provided monthly. Viral load (VL) testing will be conducted every 3 months and drug resistance testing conducted if VL ≥ 200 copies/ml. Three hundred and sixty-two participants aged ≥15 years and 30 participants aged 3–14 years with major dolutegravir-associated drug resistant mutations (DRMs) will be enrolled into the RCT and randomised to switch to ritonavir boosted darunavir (DRV/r) or continue with dolutegravir with follow-up for 12 months. VL will be measured at 1, 3, 6 and 12 months and tenofovir levels assessed on dried blood spots at month 1 and month 6. The primary outcome of the cohort is the proportion of participants achieving viral load <200 copies/ml by month 12 and the primary endpoint of the RCT is viral load <200copies/ml at 6 months using a modified FDA snap shot algorithm. Secondary endpoints are DRM patterns associated with non-suppression, level of adherence associated with suppression as well as participant and provider experiences of staying on DTG versus switching to DRV/r. The RCT primary efficacy analysis will be conducted on the Intent-to-Treat Exposed (ITT-E) population and will compare the difference in the proportion of participants with viral load <200 copies/ml 6 months after randomisation between the treatment arms stratified by the randomisation stratification factors. This study is registered at ClinicalTrials.gov, NCT06762054 (cohort) and NCT06747507 (RCT) and enrollment into the cohort started in March 2025. Conclusion: The Ndovu study will address critical gaps in the management of DTG failure including the emergence, determinants and implications of DTG resistance. Further, it will evaluate the optimal ART regimens to use in the setting of DTG resistance in adults and children.

Background: HIV-1 drug resistance (HIVDR) threatens the durability of antiretroviral therapy (ART) programmes in sub-Saharan Africa, where non-B subtypes predominate, yet national data linking mutational patterns to patient-level correlates remain scarce. Methods: We analysed 521 Kenyan patients with confirmed virologic failure referred for genotypic resistance testing (2020–2025). Resistance was interpreted with the Stanford HIVdb (v10.1), and pairwise dependencies between high-level resistance classes were quantified descriptively with mutual information (MI) normalised to marginal entropy. Multivariable logistic regression identified factors associated with high-level NRTI resistance in patients with complete covariate data (n = 299). Results: High-level resistance was present in 386 patients (74.1%, 95% CI 70.2–77.7) for NRTIs, 401 (77.0%, 73.2–80.4) for NNRTIs and 179 (34.4%, 30.4–38.5) for PIs; M184V (65.3%) and K103N (34.9%) predominated. NRTI and PI resistance co-accumulated (MI = 0.121 nats, 19% of PI entropy), whereas dependencies involving NNRTI resistance were weak (MI = 0.015, 3%). Older age was the only factor associated with high-level NRTI resistance (adjusted OR 1.05 per year, 95% CI 1.02–1.08); neither subtype nor NRTI backbone was. Conclusions: Extensive multiclass resistance is already established at virologic failure, supporting earlier failure detection, timely regimen switching and expanded access to dolutegravir-based regimens.