gonorrhoeae: gonorrhoeae Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

gonorrhoeae Bayesian Network

Description

Policy, practice, and prediction: model-based approaches to evaluating N. gonorrhoeae antibiotic susceptibility test uptake in Australia.

Format

A discrete Bayesian network to simulate the clinician-patient dynamics influencing antibiotic susceptibility test initiation. The probabilities were given within the referenced paper. The vertices are:

ASTTest

(Initiated, Not initiated);

ClinicianExperience

(Experienced, Unexperienced);

EpidemiologicalFactors

(High risk group, Low risk group);

InitialTreatmentFailure

(Treatment success, Treatment failure);

MedicationAdherence

(Proper Adherence, Improper Adherence);

NumberPartners

(One, Two to five, More than six);

PastDiagnoses

(One, Two to four, five to nine, More than ten);

PersistingSymptoms

(Symptoms persist, Symptoms resolve);

SexualOrientation

(Heterosexual, Homosexual);

UnpromptedTest

(Initiated, Not initiated);

Value

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

References

Do, P. C., Assefa, Y. A., Batikawai, S. M., Abate, M. A., & Reid, S. A. (2024). Policy, practice, and prediction: model-based approaches to evaluating N. gonorrhoeae antibiotic susceptibility test uptake in Australia. BMC Infectious Diseases, 24(1), 498.

bnRep documentation built on April 12, 2025, 1:13 a.m.