Quantifying the risks versus benefits of the Pfizer COVID-19 vaccine in Australia: a Bayesian network analysis (preprint)

ABSTRACT

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 challenge for risk-benefit analysis of vaccination programs. 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. The model estimates that in a population where 5% were unvaccinated, 5% had one dose, 60% had two doses and 30% had three doses, the probabilities of developing and dying from COVID-19-related myocarditis were 239-5847 and 1430-384,684 times higher (depending on age and sex), respectively, than developing vaccine-associated myocarditis. For one million people with this vaccine coverage, where transmission intensity was equivalent to 10% chance of infection over two months, 68,813 symptomatic COVID-19 cases and 981 deaths would be prevented, with 42 and 16 expected cases of vaccine-associated myocarditis in males and females, respectively. The model may be updated to include emerging best evidence, data pertinent to different countries or vaccines, and other outcomes such as long COVID.