About the Author(s)


Argwings O. Miruka Email symbol
Department of Public Health and Community Development, Faculty of Public Health, Maseno University, Kisumu, Kenya

Louisa N. Ndunyu symbol
Department of Public Health and Community Development, Faculty of Public Health, Maseno University, Kisumu, Kenya

Patrick O. Onyango symbol
Department of Physical and Biological Sciences, Faculty of Biological Sciences, Maseno University, Kisumu, Kenya

Citation


Miruka AO, Ndunyu LN, Onyango PO. Factors associated with drug resistance mutations among antiretroviral therapy-experienced adolescents living with HIV in South Rift Valley, Kenya. J Public Health Africa. 2025;16(4), a1488. https://doi.org/10.4102/jphia.v16i4.1488

Note: The manuscript is a contribution to the themed collection titled ‘Strengthening Scientific Publication Capacity of African Researchers’, under the expert guidance of guest editor Prof. Peter Nyasulu.

Original Research

Factors associated with drug resistance mutations among antiretroviral therapy-experienced adolescents living with HIV in South Rift Valley, Kenya

Argwings O. Miruka, Louisa N. Ndunyu, Patrick O. Onyango

Received: 27 May 2025; Accepted: 21 Oct. 2025; Published: 28 Nov. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: Antiretroviral therapy (ART) has significantly improved survival among people living with human immunodeficiency virus (PLHIV), yet drug resistance mutations (DRMs) continue to threaten treatment outcomes globally. Adolescents remain particularly vulnerable to DRMs due to biological, behavioural and structural factors. However, little is known about the factors associated with DRMs in the South Rift Valley (SRV) of Kenya.

Aim: To assess factors associated with DRMs among ART-experienced adolescents in SRV.

Setting: Eighty-two HIV clinics located in Nandi, Kericho, Bomet and Narok counties in Kenya’s SRV region.

Methods: A retrospective cohort study was conducted among 226 ART-experienced adolescents aged 10–19 years with virologic failure, selected through simple random sampling. Plasma samples were genotyped to identify HIVDRMs using the Stanford HIV Drug Resistance database. Demographic, clinical and behavioural information was obtained from medical records and questionnaires. Descriptive statistics, Chi-square tests and logistic regression were performed to determine factors associated with DRMs.

Results: The median age was 17 years (IQR: 15–18); 51.3% was male and 65% was orphans. Bivariate analysis identified several factors significantly associated with DRMs: ART duration (p = 0.030), enhanced adherence counselling (EAC) sessions (p = 0.001), ART regimen type (p = 0.001), CD4 count (p = 0.030), caregiver occupation (p = 0.029), and orphan status (p = 0.049).

Conclusion: Longer ART duration, multiple EAC sessions and use of non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimens were associated with DRMs. These findings underscore the need for strengthened adherence support, early regimen optimisation and targeted interventions for adolescents at higher risk of resistance.

Contribution: The study provides evidence to guide clinical and policy strategies aimed at improving ART outcomes among adolescents in Kenya.

Keywords: ART; HIV; EAC; CD4; drug resistance; adolescents; SRV; Kenya.

Introduction

Adolescents and young people account for a significant proportion of people living with HIV (PLHIV) globally. Of the 1.75 million adolescents living with HIV (ALHIV), about 84% reside in sub-Saharan Africa (SSA).1,2 Despite significant progress in expanding access to antiretroviral therapy (ART), adolescents continue to experience poorer treatment outcomes than adults, characterised by lower rates of viral suppression and higher risk of treatment failure.2 In Kenya, viral suppression among adolescents aged 10–19 years remains below national targets, reflecting persistent challenges in adherence, retention in care and timely detection of treatment failure.3 These gaps contribute to the emergence and accumulation of HIV drug resistance mutations (HIVDRM), which threaten the long-term effectiveness of ART programmes.

HIV drug resistance mutations occur when genetic changes in the virus reduce or eliminate the efficacy of ART.4 Contributing factors include suboptimal adherence, high viral load, low cluster of differentiation 4 (CD4) count, co-morbidities, psychosocial, behavioural, advanced HIV disease (AHD) and health system challenges such as inappropriate regimen selection, dosing errors and drug stock-outs.5,6,7

Although adherence to ART remains vital for achieving viral suppression, measuring it accurately is difficult.8 Enhanced adherence counselling (EAC), recommended by World Health Organization (WHO) for individuals with viral load > 1000 copies/mL after 3–6 months on ART,6 aims to address adherence barriers, though its effectiveness among adolescents remains uncertain.

Kenya’s ART guidelines have evolved from non-nucleoside reverse transcriptase inhibitors (NNRTI)-based regimens to dolutegravir (DTG)-based combinations since 2019.6 While DTG regimens have demonstrated strong viral suppression, emerging reports indicate possible integrase strand inhibitors (INSTI) resistance.9 A meta-analysis among treatment-experienced children and adolescents in SSA found resistance rates of 65.9% for NNRTI and 63.8% for protease inhibitor (PI),10 highlighting the need for regional data on newer regimens, particularly in Kenya’s South Rift Valley (SRV).

Monitoring ART effectiveness now primarily relies on viral load testing, though CD4 counts remain essential for identifying AHD and predicting treatment outcomes.8,11,12 Socio-economic and caregiver-related factors, including occupation, household stability and orphan status, may influence treatment adherence leading to the risk of HIVDRM.13,14

Despite the widespread rollout of ART in Kenya, emerging evidence shows increasing HIV drug resistance (HIVDR) among adolescents, largely driven by longer duration on ART, high viral load, suboptimal adherence and inadequate EAC. These findings highlight the complex interplay between behavioural, biomedical and health systems factors influencing treatment outcomes in this age group. Adolescents represent a uniquely vulnerable group because of developmental, psychosocial and health system challenges that compromise treatment continuity and viral suppression. However, data on proportions and patterns of HIVDR in this population remain limited, particularly in the South Rift Valley (SRV) region. This study therefore aimed to determine the proportions and patterns of HIVDR and to identify biomedical, behavioural and health system factors associated with resistance among ART-experienced adolescents in the SRV, Kenya.

Research methods and design

Study area and design

The study was conducted in four counties of Nandi, Kericho, Bomet and Narok in the SRV, Kenya. Counties were purposively selected because of low viral suppression rates (75% – 84%) and availability of adolescent human immunodeficiency virus (HIV) clinics with ≥ 20 enrollees. A retrospective mixed-method design was employed, targeting 82 purposively selected ART clinics.

Study population and sampling

The study population consisted of 4154 ART-experienced adolescents aged 10–19 years old enrolled in ART clinics across the selected counties in the SRV region of Kenya. The target population included adolescents on ART who had experienced virologic failure and subsequently underwent HIVDR testing, estimated at 25% (n = 1039) of the total cohort. In addition, caregivers, eight adolescent mentors and eight healthcare workers involved in adolescent HIV care were included to provide contextual insights into adherence support and service delivery practices. Of the 544 adolescents with available HIVDR results, a total of 226 participants were proportionally recruited across the participating counties for detailed analysis.

Eligibility criteria

Adolescents were eligible for inclusion if they were aged 10–19 years old, had been on ART for at least 3 years, had attended at least one clinic visit within the preceding 3 months, had fully disclosed their HIV status and possessed documented HIVDR test results. Adolescents who had defaulted from routine clinic attendance were excluded from the study.

Genotypic HIV drug resistance testing

Genotypic HIVDR testing was performed to identify mutations in the HIV-1 genome associated with resistance to antiretroviral drugs. Upon approval by the national and regional technical working groups, blood samples were collected using a standardised national form. Plasma was separated from whole blood and used for ribonucleic acid (RNA) extraction with the PureLink Viral ribonucleic acid (RNA) and/or deoxyribonucleic acid (DNA) Mini Kit (Thermo Fisher Scientific, United States [US]).

The extracted viral RNA was reverse transcribed into complementary deoxyribonucleic acid (cDNA), followed by polymerase chain reaction (PCR) amplification of the protease and reverse transcriptase regions of the pol gene. The amplified sequences were aligned and compared with reference HIV-1 strains to detect known resistance-associated mutations. Identified mutations were interpreted using the Stanford HIV drug resistance database (HIVDB), Version 9.4 [updated 2024], available at https://hivdb.stanford.edu.

Genotypic scoring system for HIV drug resistance

We used an internationally approved genotypic scoring system as per the Stanford HIVDB where (0–9) was categorised as susceptible, (0–14) as potential low-level resistance, (15–29) as low-level resistance, (30–59) intermediate resistance and (60 or greater) as high-level resistance. The HIVDR classification was not undertaken because of the study design and objectives.

Human immunodeficiency virus trained healthcare workers supported interpretation of the mutations to determine drug resistance, and a report was generated indicating whether the virus was highly resistant, moderately resistant or sensitive to specific antiretroviral drugs. This lab report was then sent back to facilities for further management of patients depending on the results.

Data were collected through structured questionnaires and review of medical records. Trained research assistants visited the selected study sites in Kericho, Bomet, Nandi and Narok Counties within the SRV, Kenya, to administer questionnaires and abstract clinical data. The questionnaires captured demographic, socio-economic and clinical information to assess factors associated with HIVDRM. A standardised data abstraction tool and national HIVDR reporting forms were used to document participant information. Clinic staff provided patient lists stratified by pharmacy refill dates to facilitate sampling. Extracted data included laboratory results, ART history, clinical records, nutritional assessments, ART regimen and duration, enhanced adherence counselling (EAC) sessions, adherence history, CD4 cell count results, viral load measurements, HIVDR test results and HIV care and treatment history. Data collection was conducted between August and November 2024.

Statistical analysis

We aimed to assess factors associated with HIVDR among ART-experienced adolescents with virologic failure. Descriptive statistics were used to summarise demographic variables. The median and interquartile range were used to describe variables such as age, duration of ART and CD4 cell count, while frequency and proportions were used to describe reported adherence, EACs, caregivers’ occupation and orphan status. Chi-square test of independence and binary logistic regression were performed to examine the relationship between selected variables and HIVDRM. All analyses were conducted using Statistical Package for Social Sciences (SPSS) Version 27, and statistical significance was set at p ≤ 0.05.

Ethical considerations

Ethical clearance to conduct this study was obtained from the Maseno University Scientific and Ethics Review Committee (No. MSU/DRPI/MUSERC/01337/24). Research authorisation was also granted by the National Commission of Science and Technology and innovation with reference number 807303. The four county governments of Kericho, Nandi, Bomet and Narok through the Ministry of Health and the Ministry of Education granted permission for the study to be conducted in respective counties. After ethical approval was obtained, all participants (or guardians) provided written informed consent; assent was obtained from minors. Adolescents unaware of their HIV status were excluded. Mature minors (e.g., adolescent mothers) were permitted to consent for themselves as per Kenyan guidelines. The HIV drug resistance test results, which were not available in patients’ charts, were shared with the respective clinics for further management of the patients with drug resistance. The consent/assent forms and questionnaires were made available in both English and Kiswahili.

Results

Socio-demographic characteristics of antiretroviral therapy-experienced adolescents in South Rift Valley

A total of 226 participants were included for analysis. The median age was 17 years old (interquartile range [IQR]: 15–18 years old), with a range of 10–19 years old. Of these, 116 (51.3%) were male and 147 (65%) were orphans. The majority (57%) were aged 17–19 years old, followed by those aged 14–16 years old (27%), and the least represented group was 10–13 years old (16%). The sex distribution was nearly equal, with male participants constituting 51.3% and female participants 48.7%.

Almost half of the adolescents (48%) reported having caregivers engaged in informal or domestic work, while 32% had caregivers in professional or managerial positions. Smaller proportions reported caregivers in unskilled labour (3%), skilled employment (2%) or other occupations (15%).

In terms of education, 28% were enrolled in tertiary institutions, 26% in secondary school, 26% in university, 17% in primary school, and a small proportion (3%) had never attended school.

Most participants (65%) were orphans, while 35% were non-orphans. More than half (57%) resided in Kericho County, with smaller proportions from Bomet (16%), Nandi (15%) and Narok (12%) counties.

Regarding the type of caregiver, 51% of adolescents were under the care of their parents, 21 single parents, 12% by grandparents, 11% by aunt or uncle and 5% siblings, as presented in Table 1.

TABLE 1: Demographic characteristics of antiretroviral therapy-experienced adolescents (N = 226).
Bivariate analysis of factors associated with HIV drug resistance mutations among antiretroviral therapy-experienced adolescents (N = 226)

Chi-square tests were conducted to explore the relationship between selected variables and HIVDRM status. Significant associations were observed for ART regimen (p = 0.001), ART duration (p = 0.030), number of EAC sessions (p = 0.001), CD4 cell count (p = 0.030), caregiver’s occupation (p = 0.029) and orphan status (p = 0.049). These variables were subsequently included in the logistic regression model to identify independent predictors of HIVDRM. Table 2 presents the results of the bivariate logistic regression analysis.

TABLE 2: Bivariate logistic regression of factors associated with HIV drug resistance mutations among antiretroviral therapy-experienced adolescents (N = 226).
Multivariate logistic regression of independent factors associated with HIV drug resistance mutations

In the multivariate model, ART duration, ART regimen and EAC sessions remained independently associated with HIVDRM after controlling socio-demographic and clinical variables indicating caregiver occupation was independently associated with HIVDR. Adolescents whose caregivers were engaged in informal or domestic work (odds ratio [OR] = 2.16; 95% confidence interval [CI]: 1.10–4.25; p = 0.026) or in professional or managerial roles (OR = 1.98; 95% CI: 1.03–3.84; p = 0.041) had significantly higher odds of developing resistance compared to those whose caregivers were unemployed or engaged in subsistence farming.

Orphan status was also a significant predictor of resistance. Orphaned adolescents were nearly twice as likely to exhibit HIVDR compared to non-orphans (OR = 1.92; 95% CI: 1.01–3.65; p = 0.047).

Cluster of differentiation 4cell count was significantly associated with resistance status. Adolescents with CD4 counts between 501 cells/mm3 – 1000 cells/mm3 (OR = 2.04; 95% CI: 1.05–3.95; p = 0.033) and 1001 cells/mm3 – 1500 cells/mm3 (OR = 2.12; 95% CI: 1.07–4.19; p = 0.029) had higher odds of resistance compared to those with counts above 1500 cells/mm3.

Duration on ART remained a strong predictor of resistance. Those on ART for 8–11 years had more than twice the odds of developing HIVDR compared to those on ART for 1–3 years (OR = 2.48; 95% CI: 1.21–5.07; p = 0.014). The likelihood of resistance increased with longer ART exposure (Table 3).

TABLE 3: Multivariate logistic regression of factors associated with human immunodeficiency virus drug resistance among adolescents in South Rift Valley, Kenya (N = 226).
Summary interpretation

Longer ART duration, multiple EAC sessions and use of NNRTI-based regimens were independently associated with HIVDRM among ART-experienced adolescents. These findings highlight the role of treatment exposure duration, regimen type and adherence-related interventions in influencing the emergence of resistance.

Distribution and average resistance patterns across antiretroviral therapy regimen classes among antiretroviral therapy-experienced adolescents with virologic failure in South Rift Valley, Kenya

Overall, 64% of adolescents with virologic failure exhibited at least one HIVDRM. When analysed by drug class, the highest resistance was observed among NNRTIs (53%), followed by nucleoside reverse transcriptase inhibitors (NRTIs) (25%), PIs (9%) and INSTIs (7%). These proportions represent the percentage of participants harbouring at least one mutation conferring low-, intermediate- or high-level resistance to drugs within each respective class, as interpreted using the Stanford HIVDB genotypic resistance interpretation algorithm (Version 9.5, Stanford University, US).

The most prevalent NNRTI-associated mutations were K103N, Y181C and G190A, which confer high-level resistance to efavirenz (EFV) and nevirapine (NVP). Among NRTIs, M184V/I (conferring high-level resistance to lamivudine and emtricitabine) and K65R (associated with tenofovir resistance) were most frequent. Protease inhibitor-associated mutations such as M46I/L and V82A were less common, while INSTI-related mutations including G118R and R263K were detected in a few participants.

This distribution pattern reflects the historical use of NNRTI- and NRTI-based first-line regimens in Kenya and the gradual transition toward DTG-based combinations. The findings are consistent with patterns reported in WHO HIVDR Reports (2021), showing persistent NNRTI/NRTI resistance among ART-experienced populations in SSA. The results are presented in Figure 1.

FIGURE 1: Distribution and average resistance patterns across antiretroviral therapy regimen classes among antiretroviral therapy-experienced adolescents with virologic failure in South Rift Valley, Kenya.

The highest resistance frequency was observed among NNRTI-based regimens (n ≈ 170; 37%), followed by NRTI (n ≈ 70; 21%), PI-based regimens (n ≈ 40; 30%) and INSTI (n ≈ 15; 7%). Non-nucleoside reverse transcriptase inhibitors resistance remains predominant, reflecting historical reliance on EFV and NVP-based therapies. Nucleoside reverse transcriptase inhibitors-associated resistance, primarily driven by M184V and K65R mutations, remains substantial, while emerging PI and INSTI resistance suggests gradual accumulation of resistance mutations under prolonged ART exposure.

Drug susceptibility profiles among antiretroviral therapy-experienced adolescents based on stanford genotypic susceptibility scores

Our analysis of genotypic susceptibility scores revealed substantial variation in predicted drug efficacy across antiretroviral drugs (ARV) classes among ART-experienced adolescents. The NRTI backbone showed moderate preservation of activity, with zidovudine (AZT) and abacavir (ABC) retaining full susceptibility in over half of participants, while lamivudine (3TC)/emtricitabine (FTC) exhibited high-level resistance in more than one-third of cases, primarily driven by the M184V/I mutation. Tenofovir maintained partial activity in most participants, suggesting it remains a viable component in second-line combinations.

In contrast, the NNRTI class demonstrated extensive loss of efficacy, with EFV and NVP showing high-level resistance in over two-thirds of adolescents, consistent with the widespread presence of K103N and Y181C mutations. However, newer NNRTIs such as etravirine (ETR) and rilpivirine (RPV) retained partial to full activity in approximately 60% of participants, indicating some potential for salvage use.

The PI and INSTI classes showed strong preservation of susceptibility. Over 85% of participants remained fully susceptible to boosted PIs lopinavir/ritonavir (LPV/r), atazanavir/ritonavir (ATV/r), darunavir/ritonavir (DRV/r) and over 90% to INSTIs (DTG, raltegravir [RAL], cabotegravir [CAB]), highlighting their high genetic barrier to resistance. These findings underscore the effectiveness of DTG-based regimens and the importance of maintaining adherence to prevent resistance emergence in these potent drug classes.

Collectively, the results reflect a shift from extensive NNRTI-associated resistance toward sustained efficacy of INSTI-based regimens, aligning with global HIV treatment guidelines and supporting the transition to DTG-anchored therapy for adolescents in Kenya and similar high-burden settings. These results are presented in Table 4.

TABLE 4: Summary of drug susceptibility profiles among antiretroviral therapy-experienced adolescents based on Stanford Genotypic Susceptibility Scores.

Discussion

We aimed to assess the factors associated with HIVDRM among ART-experienced adolescents in SRV, Kenya. We identified multiple factors that are significantly associated with drug resistance among ART-experienced adolescents in South Rift Valley region, Kenya. Key among them included long ART duration, low participation in EAC sessions, low CD4 count, (NRTI plus NNRTI)-based ART regimen type, caregiver informal employment and being orphaned. Interestingly, we also found reported adherence was not significantly associated with resistance, despite nearly 70% of participants reporting adherence challenges.

A statistically significant association was observed between ART duration and DRM, with participants on ART for more than 3 years showing higher rates of drug resistance. Although logistic regression analysis did not find a statistically significant effect of ART duration on resistance, adolescents with resistance had longer than average durations on ART. This trend aligns with prior studies linking longer ART exposure to poor adherence, treatment fatigue, virologic failure and emergence of drug resistance.12 Other studies have also shown that adolescents on ART for over 2 years have significantly higher odds of developing resistance,13 often necessitating more complex and costlier second-line or third-line regimens.13 The extended duration of ART observed in this study (up to 16 years) underscores the need for long-term adherence support, especially given the challenges of retention in care during adolescence.

Enhanced adherence counselling is a structured intervention designed to improve adherence among individuals with high viral loads. World Health Organization recommends EAC for PLHIV who have high viral load.14 We found EAC was significantly associated with resistance in our study. This is consistent with other findings showing that those who undergo EAC are likely to achieve viral suppression and rarely develop drug resistance.15 However, a recent study showed health facilities are struggling to enrol PLHIV into EAC sessions.16 In our study, adolescents who had received only one EAC session were more likely to harbour drug resistance mutations (DRM) than those who received three or more sessions. This suggests that limited or delayed engagement with adherence support may be insufficient to prevent resistance. Kenya’s test and treat policy and default regimen transitions to Tenofovir, Lamivudine and Dolutegravir (TLD) further highlight the importance of timely and robust adherence interventions.

Interestingly, reported adherence was not significantly associated with resistance, despite nearly 70% of participants reporting adherence challenges; however, another similar study showed significant association between adherence to ART and HIVDR.17 Other findings also showed adherence among adolescents was low, which is a risk factor for drug resistance.18 Our study findings highlight the limitations of reported adherence data and support evidence that caregiver support plays a vital role in adherence. As children mature into adolescence, the reduction in direct caregiver supervision may negatively impact treatment consistency, even as the need for emotional and logistical support remains high.

In terms of ART regimens, adolescents on NRTI or NNRTI-based therapies had higher rates of resistance compared to those on PI or INSTI. These results are consistent with studies indicating that NNRTI-based regimens have a lower genetic barrier to resistance.19 Similar findings were shown in a pooled analysis of PI-based failures in SSA, 17% of patients had at least one major PI resistance mutation at treatment failure,20 while other similar studies indicated about 64% of adolescents had more than 3% resistance to PI-based regimens.10 Other similar studies also detected low-level resistance to any INSTI-based regimen.21 While data on INSTI resistance in adolescents remain limited, our findings suggest emerging resistance to these newer regimens. This is concerning, given the limited therapeutic options in Kenya and the global push by WHO to transition patients to INSTI-based treatment.6 We did not include treatment regimen changes over time, since historical regimen-switch data were incomplete for a proportion of participants, limiting the feasibility of including this variable in the multivariate models. Classification of HIVDR as transmitted, acquired or pre-treatment was not performed, as this study focused primarily on identifying and describing the presence and patterns of resistance mutations among ART-experienced adolescents rather than classifying resistance types.

We also recommend future longitudinal studies to incorporate detailed regimen history to strengthen causal inferences.

Cluster of differentiation 4 cell count was also significantly associated with drug resistance. Adolescents with lower CD4 counts were more likely to have resistance mutations, corroborating prior studies from China and other regions.18 Low CD4 cell counts are indicative of immunosuppression and are associated with increased viral replication, which fosters development of resistance.18 Despite the current emphasis on viral load monitoring, our findings support the continued relevance of CD4 testing, particularly for managing advanced HIV disease.

Caregivers’ occupation also influenced drug resistance outcomes. Adolescents whose caregivers were engaged in informal or domestic work were more likely to develop resistance than those with caregivers in skilled employment. A similar study conducted in Tanzania among adolescents experiencing virologic failure also demonstrated presence of HIV drug resistance.22 Individuals who are engaged in informal employment also have low literacy level, which may contribute to inadequate knowledge of HIV. Other findings indicate caregivers’ understanding of HIV care and social support networks significantly impact adolescents’ adherence to treatment.23 This may reflect on broader socio-economic challenges affecting access to consistent care, transportation and medication adherence.

Orphaned adolescents had significantly higher rates of resistance, and those living with parents were significantly more likely to be in the non-resistance group. This suggests that targeted interventions addressing unique psychosocial support dynamics among non-orphans may be necessary to reduce the risk of drug resistance.

While literature presents mixed evidence on the impact of biological versus non-biological caregivers,14,24 Adherence behavior is influenced by factors including characteristics of adolescent, caregiver(s), and family.25 Our findings suggest the presence of a biological parent may offer emotional and practical support that improves adherence. However, other factors, such as family structure, stigma and socio-economic conditions, may also contribute to these outcomes and warrant further investigations in larger cohorts.

This study adds to the growing body of evidence by identifying factors associated with HIVDR among ART-experienced adolescents in South Rift Valley, Kenya.

Conclusion

We identified multiple factors that are significantly associated with HIVDR among ART-experienced adolescents in South Rift Valley, Kenya. Key among them include longer ART duration, inadequate participation in EAC sessions, low CD4 count, NNRTI-based regimen type, caregiver informal employment and being orphaned. These findings underscore the importance of targeted adherence support, timely regimen optimisation and socio-economic interventions to mitigate resistance and improve treatment outcomes for ALHIV.

Acknowledgements

The authors are grateful to Christopher Ochieng from laboratory molecular department for compiling drug resistance results and the research assistants, Valentine Bwogo, Consolata Seela, Francis Rono, Nancy Chepkirui and Viola Keter for coordination and logistical support during data collection.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

CRediT authorship contribution

Argwings O. Miruka: Conceptualisation, Methodology, Investigation, Data curation, Validation, Formal analysis, Writing – original draft, Funding acquisition, Resources. Louisa N. Ndunyu: Investigation, Supervision, Project administration, Writing – review & editing. Patrick O. Onyango: Investigation, Supervision, Project administration, Writing – review & editing.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The datasets used and/or analysed are available from the corresponding author, Argwings O. Miruka, on request.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

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