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Introduction: Adolescent girls and young women (AGYW) living with HIV experience poor HIV outcomes and high rates of unintended pregnancy. Little is known about which healthcare provisions can optimize their HIV‐related outcomes, particularly among AGYW mothers. Methods: Eligible 12‐ to 24‐year‐old AGYW living with HIV from 61 health facilities in a South African district completed a survey in 2018–2019 (90% recruited). Analysing surveys and medical records from n = 774 participants, we investigated associations of multiple HIV‐related outcomes (past‐week adherence, consistent clinic attendance, uninterrupted treatment, no tuberculosis [TB] and viral suppression) with seven healthcare provisions: no antiretroviral therapy (ART) stockouts, kind and respectful providers, support groups, short travel time, short waiting time, confidentiality, and safe and affordable facilities. Further, we compared HIV‐related outcomes and healthcare provisions between mothers (n = 336) and nulliparous participants (n = 438). Analyses used multivariable regression models, accounting for multiple outcomes. Results: HIV‐related outcomes were poor, especially among mothers. In multivariable analyses, two healthcare provisions were "accelerators," associated with multiple improved outcomes, with similar results among mothers. Safe and affordable facilities, and kind and respectful staff were associated with higher predicted probabilities of HIV‐related outcomes (p<0.001): past‐week adherence (62% when neither accelerator was reported to 87% with both accelerators reported), clinic attendance (71%−89%), uninterrupted ART treatment (57%−85%), no TB symptoms (49%−70%) and viral suppression (60%−77%). Conclusions: Accessible and adolescent‐responsive healthcare is critical to improving HIV‐related outcomes, reducing morbidity, mortality and onward HIV transmission among AGYW. Combining these provisions can maximize benefits, especially for AGYW mothers. [ABSTRACT FROM AUTHOR]

Introduction: Several HIV risk scores have been developed to identify individuals for prioritized HIV prevention in sub‐Saharan Africa. We systematically reviewed HIV risk scores to: (1) identify factors that consistently predicted incident HIV infection, (2) review inclusion of community‐level HIV risk in predictive models and (3) examine predictive performance. Methods: We searched nine databases from inception until 15 February 2021 for studies developing and/or validating HIV risk scores among the heterosexual adult population in sub‐Saharan Africa. Studies not prospectively observing seroconversion or recruiting only key populations were excluded. Record screening, data extraction and critical appraisal were conducted in duplicate. We used random‐effects meta‐analysis to summarize hazard ratios and the area under the receiver‐operating characteristic curve (AUC‐ROC). Results: From 1563 initial search records, we identified 14 risk scores in 13 studies. Seven studies were among sexually active women using contraceptives enrolled in randomized‐controlled trials, three among adolescent girls and young women (AGYW) and three among cohorts enrolling both men and women. Consistently identified HIV prognostic factors among women were younger age (pooled adjusted hazard ratio: 1.62 [95% confidence interval: 1.17, 2.23], compared to above 25), single/not cohabiting with primary partners (2.33 [1.73, 3.13]) and having sexually transmitted infections (STIs) at baseline (HSV‐2: 1.67 [1.34, 2.09]; curable STIs: 1.45 [1.17; 1.79]). Among AGYW, only STIs were consistently associated with higher incidence, but studies were limited (n = 3). Community‐level HIV prevalence or unsuppressed viral load strongly predicted incidence but was only considered in 3 of 11 multi‐site studies. The AUC‐ROC ranged from 0.56 to 0.79 on the model development sets. Only the VOICE score was externally validated by multiple studies, with pooled AUC‐ROC 0.626 [0.588, 0.663] (I2: 64.02%). Conclusions: Younger age, non‐cohabiting and recent STIs were consistently identified as predicting future HIV infection. Both community HIV burden and individual factors should be considered to quantify HIV risk. However, HIV risk scores had only low‐to‐moderate discriminatory ability and uncertain generalizability, limiting their programmatic utility. Further evidence on the relative value of specific risk factors, studies populations not restricted to "at‐risk" individuals and data outside South Africa will improve the evidence base for risk differentiation in HIV prevention programmes. PROSPERO Number: CRD42021236367 [ABSTRACT FROM AUTHOR]