Student Spotlight: Sophia Bahad, M2
Sophia Bahad is a current M2 student and 2025 MSSRP researcher. This past summer she presented her poster at the Boston Medical Center Pediatric Research Day titled, “Comparing Area-Based Sociodemographic Measures and Their Association with Latent TB Infection at Boston Medical Center.” Mentored by Dr. Jeffrey Campbell in the Pediatric Infectious Disease Department at BMC, Sophia’s research rethinks how the “household” is defined in latent tuberculosis infection (LTBI) prevention and care. LTBI often clusters within households, yet households are typically treated as static, co-residential units in clinical care. Using a mixed-methods approach, Sophia’s project characterizes household composition and fluidity among patients with LTBI in Boston and examines how household structure relates to disclosure patterns and TB-relevant risk factors. Based on patient interviews, she created participant-centered household diagrams to develop household membership phenotypes that may inform more effective household-level LTBI care strategies. Sophia also notes the project’s research assistants, Ariane Garing and Dorine Lavache, who were instrumental to study execution and data collection.
Sophia studied medical anthropology as an undergraduate at Boston University, where she became deeply interested in how social context shapes health behaviors and outcomes. Medical anthropology helped Sophia understand why systems function the way they do; she carried this outlook into her medical school research. Through this project, Sophia translated that lens into practical, clinically relevant TB care work. Household-centered TB prevention depends on understanding who patients actually consider part of their household and who they choose to disclose their diagnosis to. Their findings show that real-world households are dynamic networks rather than fixed residential units, which has direct implications for how LTBI screening, treatment, and support are delivered. This is especially important in diverse, migrant-rich settings where tr
aditional household definitions may miss key relationships.
Through her research experience, Sophia learned how differently qualitative and quantitative methods generate insight, and how essential both are for understanding health and disease. Working directly with patient narratives, diagrams, and lived experiences showed her how qualitative data provides context and meaning that large datasets often cannot capture alone. In contrast, earlier quantitative work using R to analyze area-based sociodemographic indices taught me how structured data can reveal population-level patterns, and together these experiences showed me the value of integrating multiple methods with strong mentorship guiding the process.
Sophia is currently preparing to present this household-focused project at the 2026 Medical Student Research Symposium.