key: cord-0700870-l3pw80rl authors: Toska, Elona; Zhou, Siyanai; Laurenzi, Christina A.; Haghighat, Roxanna; Saal, Wylene; Gulaid, Laurie; Cluver, Lucie title: Predictors of secondary HIV transmission risk in a cohort of adolescents living with HIV in South Africa date: 2022-02-01 journal: AIDS DOI: 10.1097/qad.0000000000003044 sha: 9b8c99bce5ae38eda6bdec249157aaf7c3a57db9 doc_id: 700870 cord_uid: l3pw80rl Preventing secondary HIV transmission from adolescents and young people living with HIV (AYPLHIV) to their partners and children is critical to interrupting the HIV infection cycle in sub-Saharan Africa. We investigated predictors of secondary HIV transmission risk (past-year sexual risk combined with past-year viremia) among AYPLHIV in South Africa. DESIGN: A prospective cohort of AYLPHIV in South Africa recruited n = 1046 participants in 2014–2015, 93.6% of whom were followed up in 2016–2017 (1.5% mortality). Questionnaires used validated scales where available and biomarkers were extracted from n = 67 health facilities. METHODS: Multivariate logistic regressions tested baseline factors associated with secondary HIV transmission risk, controlling for covariates, with marginal effect modelling combinations. RESULTS: About 14.2% of AYPLHIV reported high secondary HIV transmission risk. High-risk AYPLHIV were more likely to be sexually infected [adjusted odds ratio (aOR) 2.79, 95% confidence interval (95% CI) 1.66–4.68, P < 0.001], and report hunger (aOR 1.93, 95% CI 1.18–3.14, P = 0.008) and substance use (aOR 2.19, 95% CI 1.19–4.02, P = 0.012). They were more likely to be in power-inequitable relationships (aOR 1.77, 95% CI 1.08–2.92, P = 0.025) and be parents (aOR 4.30, 95% CI 2.16–8.57, P < 0.001). Adolescents reporting none of these factors had a 4% probability of secondary transmission risk, rising to 89% probability with all five identified factors. Older age and early sexual debut were also strongly associated with a higher risk of secondary HIV transmission. CONCLUSION: It is essential to identify and support AYPLHIV at a high risk of secondary transmission. Screening for factors such as mode of infection and parenthood during routine healthcare visits could help identify and provide resources to the most at-risk adolescents. Adolescents and young people living with HIV (AYPLHIV) are central to our HIV prevention agenda. Adolescents have lower rates of antiretroviral treatment (ART) adherence and poorer treatment outcomes than both children and adults [1] [2] [3] . Moreover, adolescence is a life-stage characterized by exploring relationships and testing boundaries. As AYPLHIV enter adulthood, explore sexual and romantic relationships, and initiate childbearing [4] , they also face three interrelated risks: the risk of reinfection with other strains of the virus [5] , the risk of their sexual partners becoming infected with HIV (secondary transmission) [6] and increased risks that their children will become infected with HIV [7] [8] [9] . Early data from an HIV prevention trial in Rakai, Uganda, in the late 1990s found that transmission risk rates were highest among 15 to 19-year-old adolescents living with HIV compared with older participants [10] . However, no quantitative studies to date have focused on examining factors associated with secondary transmission among AYPLHIV in sub-Saharan Africa. There is some evidence on proxy measures of secondary transmission risk individually: sexual risk or nonadherence/viral suppression. A growing body of research has documented factors associated with ART nonadherence and lack of viral suppression in this age group [11] [12] [13] , including substance use [13, 14] and complex romantic and sexual relationships [15, 16] . There is mixed evidence surrounding potential predictors of sexual risk-taking among AYPLHIV, with no longitudinal data from sub-Saharan Africa. Several crosssectional Africa-based studies have identified factors that are associated with sexual risk-taking, including older age, rural residence [17, 18] , parental monitoring, vertical infection [17] , substance use [19, 20] and power-inequitable sexual relationships in adolescence [21] [22] [23] . But transmission risk is substantially increased by the combination of sexual risk-taking and detectable viral load. No known studies in sub-Saharan Africa have reported on composite risk measures, accounting for both high-risk sex and viral load levels [17, 24, 25] . Identifying AYPLHIV at risk of secondary transmission is essential in order to interrupt the HIV transmission cycle. AYPLHIV in resource-constrained settings have limited access to timely viral load data [26] and rarely receive integrated HIVand sexual and reproductive health (SRH) services [27] . Therefore, timely biomedical data on whether adolescents are at risk of secondary HIV transmission may not be available, particularly in resource-constrained settings. Siloed service provision may also miss opportunities to identify and link to services those AYPLHIV who are most at risk. As such, tools to identify and support AYPLHIV who may be at risk of secondary transmission, especially in resource-constrained settings, are urgently needed. To address this gap, we examined factors associated with an increased risk of secondary transmission among AYPLHIV in South Africa, sing data from a two-wave community-traced study, testing hypothesized factors that could be feasibly screened for during routine healthcare visits. This study is a prospective cohort of AYPLHIV, Mzantsi Wakho, conducted in the Eastern Cape Province in South Africa. The study catchment area is a mixed rural-urban health sub-district with an estimated HIV prevalence of 13.6% [28] . Participants (n ¼ 1046), including all ARTinitiated 10 to 19-year-olds from 52 public health facilities, were recruited at baseline in 2014-2015 (90% of all eligible participants). At follow-up, n ¼ 979 were reinterviewed (93.6% retention, 1.5% mortality, 1.4% refusals, 3.1% untraceable). To reduce recruitment bias, this study included adolescents not engaged in medical care by tracing participants in their communities (>180 villages, neighbourhoods and settlements). To minimize HIV-related stigma resulting from study participation, an additional n ¼ 467 cohabiting adolescents were interviewed with non-HIV specific questionnaires (excluded from this analysis). Informed written adolescent consent was obtained alongside caregiver consent for minors prior to study participation for both rounds of data collection. Experienced research assistants read consent forms carefully in the local language (Xhosa) or English to ensure full comprehension, even in cases of low literacy. Questionnaires were administered in English or Xhosa, based on participant preference, by highly trained researchers with experience working with vulnerable children and adolescents. In parallel, clinic-based researchers extracted participants' clinical records from 67 health facilities (primary clinics, community health centres and hospitals) in 2014-2017, following participant and caregiver consent. Participants' records across multiple facilities were individually linked using unique study identifiers. The study was developed in collaboration with South African National Departments of Health, Basic Education, Social Development; the South African National AIDS Council; UNICEF; other implementing partners including Paediatric-Adolescent Treatment Africa; and consultations with AYPLHIV. Ethical approvals were obtained from University of Oxford (SSD/CUREC2/ 12-21), University of Cape Town (UCT/CSSR/2019/ 01), the provincial Departments of Health and Basic Education, and participating health facility ethics committees. The main outcome in this study was secondary transmission risk. At both baseline and follow-up, risk was defined as the proportion of participants with past-year viremia, and reported past-year sexual risk. Past-year viremia was computed using detectable viral load defined as a viral load more than 1500 copies/ml at last measurement informed by the sexual transmission rates documented in Rakai, Uganda [10] (for participants with a viral load record) or past-week ART nonadherence (for participants with missing viral load data). These two measures were combined given poor viral load coverage in the sample [26] and strong associations between high viral load, and selfreported defaulting and nonadherence, in sub-sample analyses [17] (see Tables 1 and 2 , Supplementary Digital Content 1, http://links.lww.com/QAD/C253). Past-year sexual risk was computed on the basis of adolescent selfreport of one or more of the following: unprotected sex at last intercourse, ever had transactional sex, multiple sexual partners in the last year, last sexual partner was 5 or more years older, and ever been pregnant or made someone pregnant, all of which were adapted from a nationally representative adolescent study [29] . At each timepoint, a composite transmission risk measure of both viremia and sexual risk was computed. Each participant was allocated to one of two groups: AYPLHIV calculated as having no transmission risk at both baseline and follow-up (low transmission risk) were compared with all other adolescents (high transmission risk). Baseline measures of the following factors were included in the analyses: (1) Sociodemographic factors included adolescent age [coded as younger (ages [10] [11] [12] [13] [14] and older (ages [15] [16] [17] [18] [19] ]; sex (male/female); urban/rural residence, using census definitions [30] ; housing type (informal/formal); household poverty, measured as missing one of seven basic necessities for children and adolescents validated in a nationally representative survey [31] ; and double orphanhood (both maternal and paternal), recorded using items developed from UNICEF. Past-term school absenteeism measured the number of days the adolescent missed school in the last full school term. (2) Individual-level factors included negative peer norms, measured through a series of items assessing peer support for unsafe sex and adolescent pregnancy [32] and mental health challenges, including internalized stigma and suicidality. Internalized stigma was measured as a score more than 1 using the internalized stigma sub-scale of the ALHIV-SS, a locally adapted and validated stigma scale [33] . Suicidality was recorded as whether the adolescent had thought of a way, or tried, to kill him/ herself [34] . Substance use was measured using an item adapted from WHO's AUDIT scale reporting if the adolescent's substance use interfered with walking, talking or memory, combined with an item derived with our adolescent advisory group ('I drink alcohol to have fun, without my caregivers knowing or approving'), validated with similar populations in South Africa [35] . (3) Family-level factors included positive caregiving using a six-item sub-scale from the Alabama Parenting Questionnaire [36] , including warmth and praise from a primary caregiver; good caregiver monitoring (supervision) using a scale of 10 items from the relevant subscale of the Alabama Parenting Questionnaire, such as setting rules for times to come home; and good adolescent-caregiver communication using a scale of five items including openness and talking to the caregiver without fear. Food insecurity (hunger) was defined as a binary indicator of having enough food at home in the past week, not engaging in transactional sex for food, and not missing ART because of insufficient food. (4) HIV-specific factors included time on treatment coded as more than 1 year on treatment, knowledge of HIV-positive status based on items developed through participatory research with AYPLHIV [37] , having a treatment buddy and mode of infection. Adolescents who started treatment before age 10 were designated as vertically infected, similar to existing sub-Saharan African paediatric HIV cohorts [38] , validated through an algorithm reported elsewhere [39] . Relationship factors included early sexual debut (