Computational Models and Simulations of Epidemic Infectious Diseases

In this episode of the Data Exchange I speak with Bruno Gonçalves, a data scientist working at the intersection of Data Science and Finance. I have known Bruno for several years and we met when I recruited him to teach several extremely popular conference tutorials and talks on machine learning and deep learning. Prior to shifting over to data science, he spent several years as a researcher focused on mathematical models in Epidemiology – a field with a rich history dating as far back as the 1920s.  This episode is devoted to tools and techniques for modeling epidemics.

Our conversation covered:

• Bruno’s background and his experience in modeling epidemics.
• The field of epidemic models: what techniques are used, the size of the community of researchers, and how do models get evaluated.
• His two recent posts: “Epidemic Modeling 101 – Or why your CoVID-19 exponential fits are wrong” and  “Epidemic Modeling 102 – All CoVID-19 models are wrong, but some are useful”
• The role that epidemic models play in decision making.

Detailed show notes can be found on The Data Exchange web site.

Subscribe to The Data Exchange Newsletter.