Data Science Lunch and Learn: Fitting the COVID curves


October 19, 2020

This is part 3 of a 4 part series on dealing with COVID case data. Don’t worry, you should be able to follow this session by itself and you can always find the replays here.

During the early stages of the COVID pandemic there was a lot of discussion about flattening the curve, to prevent overload on our health care system. So what exactly is that curve, and how do you fit it to the raw case report data coming in? We will discuss several approaches and show you when and how they work. In addition, we will discuss a novel approach to consider the nature of an outbreak, resulting in a clustering showing the underlying outbreaks in the aggregated data for a region. More advanced stuff, but you should be able to follow with a bit of statistics and high school maths.

We will run a Jupyter notebook in Watson Studio. If you want to try this out for yourself, please go here to sign up for a free account and follow these instructions to get up and running.


Damiaan Zwietering

Margriet Groenendijk