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ME 233: Data-driven modeling of COVID-19

How to design computational tools to understand the dynamics of the COVID-19 pandemic. Emphasis on mathematical epidemiology, infectious disease models, concepts of effective reproduction number and herd immunity, network modeling, outbreak dynamics and outbreak control, Bayesian methods, model calibration and validation, prediction and uncertaintly quantification; Projects on statistic or mechanistic modeling of COVID-19.
Terms: Aut | Units: 3
Instructors: Kuhl, E. (PI)
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