Latent Markov Modeling of HIV Vulnerability Transitions Among Adolescent Girls and Young Women in Zimbabwe

This study uses applied Latent Markov modeling (LMM) to assess longitudinal transitions in HIV vulnerability among adolescent girls and young women (AGYW) enrolled in the Determined, Resilient, Empowered, AIDS-free, Mentored, and Safe (DREAMS) program across nine districts in Zimbabwe, from October 2023 to September 2024. Using routinely collected program data for 4,341 AGYW aged 10--19 years, the analysis identified distinct latent classes of HIV vulnerability and tracked their transitions over a 12-month period. For AGYW aged 10--14 years, four latent classes, that is, very high, high, medium, and low risk were identified with vulnerability factors of in-school dropout risk, orphanhood, alcohol use, and exposure to violence. The probability of maintaining low-risk status was high (0.704), while the probability of transitioning from very high to high risk was comparatively modest (0.252), suggesting only limited movement out of the highest-risk category among AGYW. Among the 15-19-year-old AGYW, vulnerability to HIV was mainly driven by sexual behavior, condom use, pregnancy history, and transactional sex, with the highest probability of remaining in the same class observed in high-risk (0.819) and low-risk (0.714) states. Covariates such as area of residence and source of income significantly influenced transitions, where AGYW with family or informal income were less likely to shift to higher-risk states. Overall, the results demonstrate transitions consistent with reductions in HIV risk levels among AGYW during the period of DREAMS participation, alongside the program's social, educational, and economic empowerment components. In this study, Latent Markov modelling (LMM) was applied as a robust analytical framework for monitoring longitudinal changes in vulnerability and evaluating program impact in low-resource settings.