Epidemic modelling – Some notes, maths, and code

Simon Dobson

We’ve unexpectedly found ourselves in a situation in which the science of diseases is of critical importance to us all. On an individual level, we want to know what to expect of lockdowns, vaccines or other therapies. At a population level, we want to know how diseases become epidemics and then pandemics, and how the different strategies might influence their course. Above all, we want certainty that the disease will be conquered and the future will be better.

Scientists don’t really do certainty, though. All of science is based around the models that we construct to tell us about the things we’re interested in, and the experiments that we conduct to see whether the models match the reality on the ground. It’s this combination of model and experiment, trial and error and correction, that help us understand the world.

But what is a model of a disease? How do they work, and what can they tell us about what we can expect from epidemics and other events? I’m writing this book as an attempt to explain the one small corner of this vast field that I know something about: how to model epidemics using network science and computer simulations. It isn’t in any way comprehensive, leaving huge areas unexplored and a huge number of questions unanswered. I make it available as a work in progress in the hope that it may be useful and may encourage an interest in science.

(This version built Sat 27 Jun 2020 15:55:55 BST)