Faculty Bibliography

OBJECTIVES/OBJECTIVE:Achieving optimal adherence to antiretroviral therapy (ART) and viral suppression is still insufficient for attaining the UNAIDS 95-95-95 target of 2030, especially among adolescents with HIV (AWHIV). This study sought to develop a model to predict poor adherence risk among AWHIV and identify associated risk factors. DESIGN/METHODS:We utilized machine learning to predict future ART adherence among AWHIV leveraging its ability to analyze complex, multidimensional data. METHODS:We leveraged a dataset from a 6-year (2012-2018) longitudinal randomized control trial (RCT) with 635 AWHIV in Uganda. We evaluated six machine learning models and retained one with the highest area under receiver operating characteristic (AUROC), and area under precision-recall curve (AUPRC). We further identified principal factors associated with ART adherence based on the best model. RESULTS:The random forest model outperformed others, with mean AUROC: 0.71 [BC 95% confidence interval (CI) (0.69-0.72)] and AUPRC: 0.55 (BC 95% CI 0.53-0.58). The principal risk factors of poor adherence were poor adherence history; poverty; biological relationship to caregiver; self-concept; savings confidence; duration on ART; frequency discussing sensitive topics with caregivers; household size; economic group assignment; and school enrollment. CONCLUSION/CONCLUSIONS:Our findings support potential use of machine learning methods and sociobehavioral data for predicting poor ART adherence risk among AWHIV. The predictive tool can help identify AWHIV at the highest risk of treatment failure, and enable early targeted interventions. However, the tool is still preliminary and its accuracy could be improved by incorporating HIV phenotypic and clinical data. CLINICAL TRIAL NUMBER/BACKGROUND:ClinicalTrials.gov ID:NCT01790373.

OBJECTIVES/OBJECTIVE:Adolescents living with HIV (ALHIV) have low viral suppression levels, with 1 in 3 ALHIV experiencing virologic failure, calling for more efforts to reverse these trends. We developed and validated a model that predicts the risk of virologic failure (VF) among ALHIV. STUDY DESIGN/METHODS:Cross-sectional study. METHODS:We used baseline data from 702 ALHIV enrolled in the Suubi + Adherence cluster-randomized clinical trial. Participants were aged 10-16 years, living with HIV and aware of their HIV status, and are living with a family. We developed a risk-prediction model for VF (viral load of ≥200 copies/mL) using sociodemographic, behavioral, psychological, economic, and treatment-related factors. LASSO logistic regression using 10-fold cross-validation with bootstrapping was used to select the predictors for the final model. Model performance was assessed by determining the discrimination using the area under the curve and calibration by drawing a calibration plot. RESULTS:Using a lambda value of 0.007, the final model had 24 predictors (and interaction terms). The predictors included the participants' age, sex, work status, stigma, depressive symptoms, adherence self-efficacy, HIV knowledge, duration with HIV, time spent on ART, communication with the caregiver, family cohesion, social support, orphanhood status, number of people in the household, HIV disclosure, years spent at the current residence, and household asset ownership. The model predicted VF with AUC of 73.8 (95 % CI: 68.3-78.0) and calibration slope of 0.985. CONCLUSIONS:We developed and validated a model to predict the risk of virologic failure among ALHIV in Uganda, demonstrating its potential utility in identifying individuals at elevated risk for VF. Future models could be refined by incorporating clinical characteristics such as CD4 count to further improve predictive accuracy.

Viral load suppression (VLS) is considered crucial in the global efforts to end the HIV/AIDS pandemic and young people lag behind adults in this important indicator. However, little is known about VLS among refugee adolescents and youth (RAY), a vulnerable group, often ignored by research, with multiple intersecting risk factors and unique challenges. The goal of this study was to determine the prevalence of VLS and examine associated risk and protective factors among RAY in refugee settlements in Uganda, a country severely affected by the HIV/AIDS pandemic and currently hosting the most refugees in sub-Saharan Africa (SSA). We analyzed cross-sectional data from a pilot cluster randomized trial with 180 participants (ages 13-30) recruited from 20 health centers in three refugee settlements between July and December 2023. We employed a hierarchical (mixed-effects) logistic regression model to examine the association between selected demographic, psychosocial, and economic factors and VLS. The prevalence of VLS among RAY was very low at just 52%. Factors associated with VLS included financial stability, adherence self-efficacy, and HIV status disclosure. Having financial savings was associated with VLS (adjusted odds ratio:2.68; 95% CI: 1.48-5.11; p = 0.003). Treatment support from others including teachers and health care providers had five-fold odds of VLS (5.0, 1.64-15.24; p = 0.005). Conversely, older age and interactions between stigma/self-efficacy and stigma/HIV status disclosure were associated with viral load non-suppression. This study highlights the urgent need for tailored interventions targeting economic and psychosocial hardships like poverty, stigma, and food insecurity to enhance HIV VLS and other treatment outcomes among RAY.

INTRODUCTION/BACKGROUND:. METHODS AND ANALYSIS/METHODS:or an enhanced usual care control arm. Couples in the Mlambe arm will receive incentivised matched savings accounts and monthly sessions on financial literacy, relationship skills, and alcohol reduction education and counselling. Participants will be assessed at baseline, 11 months, 15 months and 20 months to examine effects on heavy alcohol use, HIV viral suppression, ART adherence and couple relationship dynamics. Study hypotheses will be tested using multilevel regression models, considering time points and treatment arms. Programmatic costs will be ascertained throughout the study and incremental cost-effectiveness ratios will be computed for each arm. ETHICS AND DISSEMINATION/BACKGROUND:The RCT has been approved by the University of California, San Francisco (UCSF) (Human Research Protection Program; Protocol Number 23-40642), and the study has been approved by the National Health Sciences Research Committee (NHSRC; Protocol Number 24/05/4431) in Malawi. Adverse events and remedial actions will be reported to authorities both in Malawi and at UCSF. Results will be disseminated to study participants, local health officials and HIV policy makers and through presentations at conferences and publications in peer-reviewed journals. TRIAL REGISTRATION NUMBER/BACKGROUND:ClinicalTrials.gov Protocol Registration; NCT06367348 registered on 19 April 2024; https://register. CLINICALTRIALS/RESULTS:gov/. Protocol Version 1.0: 22 October 2024.

Adolescents living with HIV (ALHIV) have low adherence to antiretroviral therapy (ART). Poverty and mental health challenges remain major drivers of this poor ART adherence. We explored the mediators of the impact of an economic empowerment intervention on ART adherence among ALHIV and assessed the moderating effects of depression. We randomized 39 clinics (702 participants) into the control or intervention groups. Participants were aged 10-16, living with HIV and taking ART. The intervention comprising matched savings account, financial literacy training, and microenterprise workshops. We fitted a sequential structural equation model to examine how the three mediators-HIV stigma, barriers to medical care, and healthcare transition readiness-influenced ART adherence at year seven. Depression was included as a moderator. At baseline, the mean age was 12 years, and only 73.0% achieved good adherence (≥ 90%). The intervention directly improved ART adherence, β = 0.060 (95% CI: 0.038, 0.081), p < 0.001. Also, there was a significant indirect effect of the intervention on ART adherence, mediated through barriers to medical care, β =  - 0.036 (95% CI: - 0.041, - 0.032), p < 0.001, and HIV stigma, β =  - 0.011 (- 0.016, - 0.007), p < 0.001. Depression reduced the effect of the intervention on ART adherence β =  - 0.114 (- 0.123, - 0.104), p < 0.001. Our results showed that providing ALHIV with financial resources improved their ART adherence; however, this was affected by depression. Therefore, programs aimed at improving outcomes in ALHIV should consider incorporating interventions that address mental health challenges in addition to poverty.

Substance use among youth is a significant public health issue, particularly in low resource settings in Sub-Saharan Africa (SSA), where it contributes to HIV transmission and poor engagement in HIV care. This study employs machine learning (ML) techniques to develop models for predicting problematic substance use (PSU) among youth living with HIV (YLHIV) in Uganda, aiming to identify important multilevel risk factors and compare predictive performance of ML algorithms. Utilizing a cross-sectional dataset of 200 YLHIV aged 18-24 in Uganda, we trained and evaluated six predictive models, through 10-fold cross validation. Model performance was assessed using area under receiver operating characteristic curve (AUROC), and precision recall curve (AUPRC). Subsequent feature importance analysis revealed key predictors of PSU. The random forest model achieved the best discriminative performance with an AUROC of 0.78 (0.01) and AUPRC of 0.75 (0.02). Key predictors of PSU spanned individual, interpersonal, and community dimensions including depression, sexual risk-taking behaviors, monthly income, adverse childhood experiences, family involvement in selling alcohol, friends enabling access to alcohol, exposure to community educational campaigns against alcohol, household size, and knowledge of alcohol effects on HIV treatment. Our findings highlight ML's potential in predicting PSU among YLHIV and provide insights to guide targeted interventions and support policy formulations mitigating PSU effects on HIV management.

BACKGROUND:Women engaged in commercial sex work (WESW) are exposed to behavioral, biological, and structural factors that exacerbate their risk of HIV infection and other sexually transmitted infections. While commercial sex work may appear voluntary, WESW are more likely to be constrained to selling sex due to limited viable alternatives. To effectively support this vulnerable group of women, it is critical to understand factors that facilitate and impede their decisions to transition from sex work into other careers or jobs. The current study explored women's decision to transition from sex work into other careers or jobs. METHODS:Face-to-face semi-structured in-depth interviews were conducted with 53 WESW aged 20-47 enrolled within the larger Kyaterekera study, a randomized clinical trial (N = 542) implemented in 19 geographical hotspots in the Southern region of Uganda. Participants were selected based on their level of intervention attendance (high/medium/low attendance) during the 12-month follow-up (Time 2). The interviews were conducted in Luganda the widely spoken language in the study area to explore the factors influencing women's decisions to transition from sex work to other jobs or careers. The main interview question used for this study was, "What are some of the factors that may influence whether you would transition from sex work to other jobs or vocations?" All interviews were audio-recorded, transcribed verbatim, and translated into English. Thematic analysis in Dedoose software was used to analyze the data. RESULTS:Participants reported three primary types of decisions, including considering leaving sex work, deciding to leave, and staying in sex work. The emerging themes from the interviews were categorized into individual and structural level facilitators and barriers to transitioning out of sex work. Individual-level factors included issues of stigma, discrimination, and aging as factors that facilitated women's decision to leave sex work. At the interpersonal level, physical and sexual violence was noted as a reason to leave sex work. At the structural level, stigma and discrimination (from community members) were identified as facilitators to leaving sex work. Income-related factors were identified mainly as barriers to leaving sex work. CONCLUSION/CONCLUSIONS:Our study highlights the complex decision-making processes among WESW as they navigate transitions to alternative jobs or careers. By advocating for multifaceted interventions and policies tailored to the diverse challenges faced by WESW, our study contributes to a more informed approach to supporting their transition out of sex work.

Sub-Saharan Africa (SSA) ranks lowest on the UNDP's Gender Inequality Index (GII), with a score of 0.56 out of 1 (1 being the worst), while Uganda scores 0.53, reflecting high gender inequality between males and females. These gender disparities are deeply rooted in longstanding inequitable gender norms and worsened by poverty. This study assessed a family economic empowerment intervention's impact on gender norm beliefs among HIV-orphaned adolescents in Uganda using three time-points data from the Suubi-Maka study, a cluster-randomized trial with 346 adolescent-caregiver dyads. Participants were randomized to control (n = 167) or treatment (n = 179) groups, with data collected at baseline, 12, and 24 months. We used mixed effects linear regression to assess the effect of the economic empowerment intervention on gender norms. Results indicated significant group-by-time interaction effects but non-significant independent group or time effects. Social support was positively significantly associated with equitable gender norms, emphasizing the role of supportive networks in facilitating change in gender norm beliefs. These findings suggest that economic interventions alone may not be sufficient for altering deeply entrenched gender norms, and future efforts should include more targeted, gender-transformative approaches.

We investigated how COVID-19-related disruptions influenced antiretroviral therapy (ART) adherence among young adults living with HIV (YALHIV) in Southern Uganda, a region with limited resources and high rates of HIV. Data were analyzed from 499 YALHIV aged 19 to 25, participating in the Suubi+Adherence-R2 COVID-19 Supplement study. The study measured COVID-19 disruptions using an 8-item Coronavirus Impact Scale and evaluated ART adherence through self-reported measures. Our analytical framework was informed by the Health Belief Model and generalized estimating equations were estimated. We find no statistically significant association between COVID-19 disruptions, as quantified by the COVID-19 Impact Score, and sub-optimal ART adherence (OR = 0.99, 95% CI [0.87-1.14]). However, findings revealed that being employed (OR = 1.99, 95% CI [1.07-3.71]) and older age (OR = 1.18, 95% CI [1.02-1.37]) was associated with higher likelihood of poor adherence highlighting the complex interplay between economic activity, working schedules, and health management. Other notable predictors included marital status, with cohabiting individuals showing decreased odds of poor adherence (OR = 0.25, 95% CI [0.08-0.74]) compared to single and separated YALHIV. These insights emphasize the need for multifaceted intervention strategies that consider both individual and systemic factors affecting ART adherence. Tailored interventions must address the socioeconomic challenges intensified by the pandemic and leverage the inherent resilience within this population to enhance ART adherence outcomes for YALHIV in challenging environments. Trial Registration ClinicalTrials.gov, ID: NCT01790373.