Policy, practice, and prediction: model-based approaches to evaluating N. gonorrhoeae antibiotic susceptibility test uptake in Australia.
An object of class bn.fit. Refer to the documentation of bnlearn for details.
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:
(Initiated, Not initiated);
(Experienced, Unexperienced);
(High risk group, Low risk group);
(Treatment success, Treatment failure);
(Proper Adherence, Improper Adherence);
(One, Two to five, More than six);
(One, Two to four, five to nine, More than ten);
(Symptoms persist, Symptoms resolve);
(Heterosexual, Homosexual);
(Initiated, Not initiated);
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.