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SUMMARY:Estimating the effectiveness of COVID-19 vaccination: target trial
  emulation using linked electronic health record data. - Jonathan Sterne (
 University of Bristol)
DTSTART:20230427T123000Z
DTEND:20230427T133000Z
UID:TALK199717@talks.cam.ac.uk
CONTACT:Spencer Keene
DESCRIPTION:The COVID-19 pandemic led to unprecedented progress in making 
 population-level\, linked electronic health record (EHR) data available to
  approved researchers. OpenSAFELY is a secure\, transparent\, open-source 
 software platform for the analysis of linked EHR data from over 24 million
  people for projects relating to the COVID-19 pandemic. This and other pla
 tforms enabled work addressing urgent\, policy-relevant questions\, such a
 s estimating the effectiveness of the COVID-19 vaccines outside clinical t
 rials. Estimating causal effects\, such as COVID-19 vaccine effectiveness\
 , from EHR data can be helped by specifying the hypothetical ‘target tri
 al’ whose results the observational data analysis is trying to emulate.\
 n\n\nThe nature of the COVID-19 vaccine rollout and the dramatic variation
  in the incidence of infection-related outcomes during the pandemic make e
 stimating vaccine effectiveness from EHR data challenging. I will describe
  approaches to estimating vaccine effectiveness based on such target trial
 s\, and results from analyses using these approaches to estimate the effec
 tiveness of first\, second and further doses of COVID-19 vaccines\, and co
 mpared different vaccine brands. This work was conducted using OpenSAFELY 
 under a collaboration between the University of Bristol\, the Bennett Inst
 itute at the University of Oxford\, the London School of Hygiene and Tropi
 cal Medicine\, and Harvard University.
LOCATION:Heart and Lung Research Institute (ground floor) or Virtually via
  Zoom
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