Influenza vaccination is our best defense against seasonal epidemics, yet vaccine effectiveness can dramatically vary between individuals. Age, exposure history, genetic background, and socio-environmental factors all shape immune responses, but current vaccine recommendations rarely account for this diversity. Using longitudinal serological and clinical data from thousands of individuals spanning infancy to old age, we apply computational modeling and causal inference to map how immunity evolves across the human lifespan. These analyses reveal modifiable drivers of vaccine response in distinct age groups and highlight strategies for personalized, adaptive vaccination. This work lays the groundwork for integrating individualized predictions into clinical practice and public health policy to improve influenza protection for all.
This seminar series is organized by the Multiscale Immune Systems Modeling (MISM) Center of Excellence, funded by NIAID/NIH (U54AI191253).
Speaker
Tal Einav, PhD
The Bodman Family Assistant Professor
Laboratory for Computational Immunology
Center for Vaccine Innovation
La Jolla Institute for Immunology
University of California San Diego
Co-sponsored by the Duke Department of Biostatistics and Bioinformatics and the Duke Biostatistics, Epidemiology, and Research Design (BERD) Methods Core, this event is also being promoted by the NC BERD Consortium. The Consortium is a collaboration of the CTSA-funded BERD cores at UNC-Chapel Hill, Wake Forest University School of Medicine, and Duke University School of Medicine.