Introduction
For decades, mathematical models describing the spread of infectious diseases have primarily been conceptual models, whose realism could be limited by the lack of data necessary to characterize the underlying processes. This symposium will explore how the integration of new types of data—whether behavioral (e.g., on human mobility, contact networks, and risk perception), biological data (e.g., multiplex serology and antigenic landscapes), or epidemiological data (e.g., digital contact tracing), has revolutionized the field of epidemic modeling, challenging traditionally held assumptions and necessitating the development of new models.