Explore mathematical modeling techniques for disease spread in this 40-minute colloquium talk from the Fields Institute. Learn how to construct historical data, implement data splitting, and utilize simple machine learning tools for training and testing models. Discover the process of determining model parameters and analyzing the relative influence of policy variables. Gain valuable insights into the application of mathematics in public health through this comprehensive overview presented by Pouria Ramazi from Brock University.
Mathematical Modeling of Diseases Spread - The Dextrous Use of Simple Machine-Learning Tools
Overview
Syllabus
Intro
Modeling disease spread
Overview
Constructing Historical Data
Data Splitting (the gap' in the data)
Training and test
Goal
Model parameters
Results!
Relative influence of the policy variables!
Concluding remarks
Taught by
Fields Institute
