Modelling infectious diseases: what can branching processes tell us?
This is a collaborative talk organised by the Department of Statistics, the Department of Computer Science and the BDI. The talk will be held on Zoom.
Mathematical descriptions of infectious disease outbreaks are fundamental to understanding how transmission occurs. Reductively, two approaches are used: individual based simulators and governing equation models, and both approaches have a multitude of pros and cons. In this talk I will connect these two worlds via general branching processes. I will discuss (at a high level) the rather beautiful mathematics that arises from these branching processes and how these can help us understand the assumptions underpinning mathematical models for infectious disease. I will then explain how this new maths can help us understand uncertainty better, and show some simple examples. This talk will be a little technical, but I will focus as much as possible on intuition and the big picture.
Date: 24 February 2022, 15:30
Venue: Venue to be announced
Speaker: Samir Bhatt, Professor of Machine Learning and Public Health (University of Copenhagen and Professor of Statistics and Public Health, Imperial College London)
Organising department: Department of Statistics
Organisers: Beverley Lane (Department of Statistics, University of Oxford), Professor Christl Donnelly (University of Oxford)
Organiser contact email address: events@stats.ox.ac.uk
Hosts: Professor Seth Flaxman (Department of Computer Science, University of Oxford), Professor Christl Donnelly (University of Oxford), Professor Christophe Fraser (University of Oxford)
Booking required?: Required
Booking url: https://www.stats.ox.ac.uk/events/joint-statistics-computer-science-bdi-talk-24th-feb-2022/
Audience: Members of the University only
Editor: Beverley Lane