A Bayesian network analysis quantifying risks versus benefits of the Pfizer COVID-19 vaccine in Australia
Jane E. Sinclair, Helen J. Mayfield, Kirsty R. Short, Samuel J. Brown, Rajesh Puranik, Kerrie Mengersen, John C. B. Litt & Colleen L. Lau
Published: 11 August 2022
Overview
The Pfizer COVID-19 vaccine is associated with increased myocarditis incidence. Constantly evolving evidence regarding incidence and case fatality of COVID-19 and myocarditis related to infection or vaccination, creates challenges for risk-benefit analysis of vaccination. Challenges are complicated further by emerging evidence of waning vaccine effectiveness, and variable effectiveness against variants.
Here, we build on previous work on the COVID-19 Risk Calculator (CoRiCal) by integrating Australian and international data to inform a Bayesian network that calculates probabilities of outcomes for the delta variant under different scenarios of Pfizer COVID-19 vaccine coverage, age groups (≥12 years), sex, community transmission intensity and vaccine effectiveness.
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Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework
Colleen Lau, Helen Mayfield, Jane Sinclair, Samuel Brown, Michael Waller, Anoop Enjeti, Andrew Baird, Kirsty Short, Kerrie Mengersen, John Litt
Published: 4 November 2021
Overview
- AZ vaccination risk-benefit analysis must consider age/community transmission level.
- AZ vaccine benefits far outweigh risks in older age groups and during high transmission.
- AZ vaccine-associated TTS has lower fatality than COVID-related atypical blood clots.
- Bayesian networks utility for risk-benefit analysis of rapidly evolving situations.
- BNs allow integrating multiple data sources when large datasets are not available.
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