corical: corical Bayesian Network

Description

Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework.

Arguments

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

Format

A discrete Bayesian network to perform risk-benefit analysis of vaccination. The probabilities were given in the referenced paper. The vertices are:

Age: (0-9, 10-19, 20-29, 30-39, 40-49, 50-59, 60-69, 70+);
AZVaccineDoses: (One, Two, Three, Four);
BackgroundCSVTOver6Weeks: (Yes, No);
BackgroundPVTOver6Weeks: (Yes, No);
Covid19AssociatedCSVT: (Yes, No);
Covid19AssociatedPVT: (Yes, No);
DieFromBackgroundCSVT: (Yes, No);
DieFromBackgroundPVT: (Yes, No);
DieFromCovid19: (Yes, No);
DieFromCovid19AssociatedCSVT: (Yes, No);
DieFromCovid19AssociatedPVT: (Yes, No);
DieFromVaccineAssociatedTTS: (Yes, No);
IntensityOfCommunityTransmission: (None, ATAGI Low, ATAGI Med, ATAGI High, One Percent, Two Percent, NSW 200 Daily, NSW 1000 Daily, VIC 1000 Daily, QLD 1000 Daily);
RiskOfSymptomaticInfection: (Yes, No);
RiskOfSymptomaticInfectionUnderCurrentTransmissionAndVaccinationStatus: (Yes, No);
SARSCoV2Variant: (Alpha Wild, Delta);
Sex: (Male, Female);
VaccineAssociatedTTS: (Yes, No);
VaccineEffectivenessAgainstDeathIfInfected: (Effective, Not Effective);
VaccineEffectivenessAgainstSymptomaticInfection: (Effective, Not Effective);

References

Lau, C. L., Mayfield, H. J., Sinclair, J. E., Brown, S. J., Waller, M., Enjeti, A. K., ... & Litt, J. (2021). Risk-benefit analysis of the AstraZeneca COVID-19 vaccine in Australia using a Bayesian network modelling framework. Vaccine, 39(51), 7429-7440.