Factors associated with engagement in HIV care for young people living with perinatally acquired HIV in England: An exploratory observational cohort study

Identifying which young people living with perinatally acquired HIV (PHIV) are less likely to engage in care is crucial to allow targeted interventions to support them to attend clinic. We adapted an existing Engagement in Care (EIC) algorithm for adults with HIV in England, for use in young people. We applied it to data from young people with PHIV in the Adolescents and Adults Living with Perinatal HIV (AALPHI) cohort. The algorithm predicts the timing of the next scheduled clinic visit, within 1-6 months of current visit, based on routine clinical data. Follow-up was 12-months from AALPHI baseline interview. Each person-month was classified as engaged in care or not. Logistic regression models (allowing for clustered data) were used to explore baseline characteristics associated with being engaged in care, adjusting for a priori variables (time from interview, sex, age, ethnicity, country of birth). Potential characteristics were across 7 domains: sociodemographic; risk behaviour practices; mental health; cognition; clinic setting; HIV management and experience; and HIV clinical markers. Of 316 young people, 187(59%) were female, 271(86%) of black ethnicity and 184(58%) born abroad. At baseline, median [IQR] age was 17[15-18] years, and 202(69%) had viral load ≤50 copies/ml(c/mL). 87% of 3,585 person-months were classified as engaged in care. Characteristics independently associated with poorer odds of being engaged in care were: Asian/mixed/other ethnicity, vs. black ethnicity (OR 0.44, 95% CI 0.25, 0.78, p = 0.02); ever self-harmed, vs. not (OR 0.55, 95% CI 0.32, 0.95, p = 0.03); on antiretroviral therapy (ART) and self-assessed bad/not so good adherence (OR 0.46, 95% CI 0.25, 0.84) or not on ART (OR 0.64, 95% CI 0.64, 1.21) vs. on ART and good/excellent adherence (p = 0.04)); baseline VL>50c/mL, vs VL≤50c/mL (OR 0.47, 95% CI 0.30, 0.75, p = 0.002). These characteristics can help identify individuals requiring enhanced support to maintain service engagement.