Causal inference, big data and public health: estimating effectiveness and quantifying waning effectiveness of COVID-19 vaccines
Effectiveness of COVID-19 vaccines was first demonstrated in randomised trials, but many questions of vital importance to vaccination policies could only be addressed in subsequent observational studies. The pandemic led to a step change in the availability of population-level linked electronic health record data, analysed in privacy-protecting Trusted Research Environments, across the UK. I will discuss methodological approaches to estimating causal effects of COVID-19 vaccines, and their application in estimating vaccine effectiveness and quantifying waning vaccine effectiveness. I will present results from recent analyses using detailed linked data on up to 24 million people in the OpenSAFELY Trusted Research Environment, which was developed by the University of Oxford’s Bennett Institute for Applied Data Science.
Date: 20 May 2022, 14:00 (Friday, 4th week, Trinity 2022)
Venue: Mathematical Institute, Woodstock Road OX2 6GG
Venue Details: L6
Speaker: Prof Jonathan Sterne (University of Bristol)
Organising department: Mathematical Institute
Organiser: Sara Jolliffe (University of Oxford)
Organiser contact email address: sara.jolliffe@maths.ox.ac.uk
Host: Dr Peter Minary (University of Oxford)
Part of: Mathematical Biology and Ecology
Booking required?: Not required
Audience: Members of the University only
Editor: Sara Jolliffe