Skip to main content

Explore the mathematics of Covid-19 and its potential impact

Here you can find a bespoke series of lectures on epidemic modelling provided by experts from the Department of Mathematical Sciences at Bath.

Mathematical sciences is a hugely important tool in exploring the nature and impact of the spread of the Covid-19, as well as predicting its future trajectory and repercussions. Staff from Maths at Bath are involved in research which is very relevant to the current situation, and the department is involved in many initiatives to support the current crisis. Here you can explore the background of epidemic modelling and find out about some of the other activities going on in Mathematical Sciences at this time.

The lectures available are:

  • The basics of models of disease spread, Kit Yates
  • Adding complexity to models of disease spread, Kit Yates
  • The lessons we can learn from mathematical models of disease spread, Kit Yates
  • An overview of the mathematical frameworks behind some influential models for the epidemiological dynamics of Covid-19, Ben Adams
  • Mathematical modelling of sneezes and coughs - or how far should you be social distancing? Phil Trinh
  • Epidemics on networks, Tim Rogers
  • Control of COVID-19: Lifting the Lockdown, Mark Opmeer

An introduction to the mathematical modelling of disease spread from Kit Yates

There are three parts to this talk. You can watch each part via the dropdown selector in the video player on the right. The notes mentioned in this lecture are available upon request from Kit Yates.

Part 1. The basics of models of disease spread.

An introduction to the mathematical modelling of the disease spread focussing on the SI and SIS models, stochastic branching processes, the basic reproduction number and the epidemic threshold theorem.

Part 2. Adding complexity to models of disease spread.

An exploration and analysis of the SIR (susceptible, infected, removed) model, used for modelling many infections diseases, and the more complex SEIR (susceptible, exposed, infected, removed) model.

Part 3. The lessons we can learn from mathematical models of disease spread.

Exploring the parameterisation of simple models and investigating the interventions that the models suggest can bring disease outbreaks under control.

Under the hood of some covid-19 epidemic models, Ben Adams

‘Everything should be made as simple as possible but not simpler.' (Occam's razor)

An overview of the mathematical frameworks behind some influential models for the epidemiological dynamics of Covid-19 from Ben Adams.

Mathematical modelling of sneezes and coughs - or how far should you be social distancing? Phil Trinh

Using classical fluid mechanics and back-of-the-envelope calculations, can we estimate how far droplets in a sneeze or cough might propagate?

Epidemics on networks, Tim Rogers

An overview of ongoing research into epidemics spreading in networks: how to predict the speed of spread and determine who is most at risk.

Control of Covid-19: Lifting the Lockdown, Mark Opmeer

Using differential equations and optimal control theory to investigate the path to lifting the lockdown.

Our research in the media

Find out about some of the mathematical approaches to tackling the Covid-19 pandemic from staff in the department.

More about mathematics at Bath

Department of Mathematical Sciences