Advanced Epidemiology of Aging

EPI 264 Subject & Catalog Number

Description

This course in the Epidemiology of Aging series deepens students' understanding of epidemiologic methods applied to complex, age-related health issues through interactive lectures, hands-on exercises, and in-depth discussions of case studies on emerging topics. Building on the foundational principles from EPI 254, this course will introduce advanced concepts and methods for novel aging research, such as the study of age, period, and cohort effects; the application of advanced causal inference methods, including natural experimental design, trial emulation, and AI-assisted causal inference; and challenges and approaches to studying the oldest-old population. Students will conduct hands-on exercises examining birth cohort effects, explore multimodal data integration, investigate common symptoms and/or conditions in older adults previously underexplored, such as seizures, falls, delirium, traumatic brain injuries, functional decline, and other geriatric symptoms/conditions, as well as discuss case studies among the growing oldest-old population. Special emphasis is placed on fostering critical thinking, applying novel analytic techniques, and leveraging real-world data (wearables, electronic health records, claims, registries) to inform public health policies, healthcare delivery, risk stratification, and intervention designs. This course is ideal for master’s and doctoral students interested in clinical epidemiology, data science, neuroepidemiology, or healthcare delivery research focused on older populations. It will also provide opportunities to conduct mentored independent studies on topics related to aging.