# Integrating spatial and non-spatial data to examine multilevel drivers of HIV risk among adolescent mothers in sub-Saharan Africa

> **NIH NIH F31** · DREXEL UNIVERSITY · 2024 · $32,974

## Abstract

PROJECT SUMMARY/ABSTRACT
 HIV transmission in sub-Saharan Africa (SSA) occurs predominantly among young people (aged 15-24
years old) and within micro-epidemics (high HIV prevalence areas). Among adolescents, girls account for 80%
of all adolescent HIV infections (15-19 years old) and adolescent mothers (AMs) are at higher HIV risk than
non-parenting girls. However, as AMs have been largely overlooked in HIV prevention research, gaps in
knowledge regarding where micro-epidemics occur among AMs and how structural (e.g., urbanization) and
relational HIV risk factors impact adolescent mothers’ HIV risk remain. Further, despite differences in AMs’
relationship configurations, no studies have examined how the co-occurrence of relational factors impact AMs’
vulnerability to HIV and unprotected sex using a typological approach. Moreover, most HIV studies on AMs in
SSA use a single-level approach to describe HIV risk as opposed to a multilevel framework that incorporates
spatial (i.e., structural factors) and non-spatial (i.e., relationship typologies, individual and familial factors) risk
factors. This exploratory study will use a modified social ecological framework to identify micro-epidemics, and
to characterize relationship typologies and multilevel factors that impact AMs’ HIV risk. The specific aims are
to: 1) characterize HIV micro-epidemics among AMs in SSA, 2) identify typologies of AMs’ sexual relationships,
and 3) assess whether multilevel factors are associated with HIV risk and unprotected sex among AMs. To
address these aims, this study will use (1) secondary data from the Population-based HIV Impact Assessment
(PHIA), which includes 2,879 AMs (aged 15-19 years old); and (2) publicly available structural-level data, from
various sources which will be linked to PHIA cluster-level data. Multiple quantitative analytic approaches will be
used to execute aims, including spatial and machine learning techniques (Aim 1), latent class analysis (Aim 2),
and mixed effects modeling (Aim 3). Study findings may inform targeted HIV prevention interventions for AMs.
This study aligns with the NICHD’s research priorities by examining structural risk factors of HIV in a high-risk
setting and the UNAIDS 95-95-95 goal. The training plan developed by the PI, sponsor Dr. Félice Lê-
Scherban, and co-sponsors Drs. Allison Groves and Alex Ezeh, supports the proposed research and the PI’s
training goals, which are to: 1) gain expertise in theoretical frameworks of social epidemiological and
adolescent health research, 2) develop methodological skills in machine learning and latent class analysis, and
3) refine research dissemination, communication, and scholarly writing skills. The PI will leverage resources at
Drexel University Dornsife School of Public Health, a collaborative and multidisciplinary institution that
prioritizes health disparities and global research. The proposed research, training, institution, and mentorship
team will support the PI’s pursuit of ...

## Key facts

- **NIH application ID:** 10922676
- **Project number:** 5F31HD111353-02
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** Luwam T Gebrekristos
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $32,974
- **Award type:** 5
- **Project period:** 2023-06-01 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10922676

## Citation

> US National Institutes of Health, RePORTER application 10922676, Integrating spatial and non-spatial data to examine multilevel drivers of HIV risk among adolescent mothers in sub-Saharan Africa (5F31HD111353-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10922676. Licensed CC0.

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