Epidemic modelling -- some notes, maths, and code

The 2020 covid-19 pandemic made it clear how much we depend on a public understanding of science. Without public confidence it's impossible to follow and maintain the sorts of strategies we need to keep us all safe in the face of a new and poorly-understood disease.

A lot of the public communications from government referred to "the science", and especially to modelling of possible disease and countermeasures scenarios. Several people asked me about what this meant: what is a disease model, how to we evaluate what they're saying, and so forth. So I decided to write an introduction to the parts of this vast and complicated subject that I know something about: epidemic spreading on networks.

To read online
Repository on Github