gonorrhoeae {bnRep} | R Documentation |
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.