Australian Gonococcal Surveillance Programme Annual Report, 2020

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

BACKGROUND

Antimicrobial resistance (AMR) represents a significant threat to global health with Neisseria gonorrhoea emerging as a key pathogen of concern. In Australia, the Australian Gonococcal Surveillance Program (AGSP) plays a critical role in monitoring resistance patterns. However, antibiotic susceptibility test (AST) uptake - a crucial component for effective resistance surveillance - remains to be a limiting factor. The study aims to model the processes involved in generating AST tests for N. gonorrhoea isolates within the Australian healthcare system and assess the potential impact of systematic and policy-level changes.

METHODS

Two models were developed. The first model was a mathematical stochastic health systems model (SHSM) and a Bayesian Belief Network (BBN) to simulate the clinician-patient dynamics influencing AST initiation. Key variables were identified through systematic literature review to inform the construction of both models. Scenario analyses were conducted with the modification of model parameters.

RESULTS

The SHSM and BBN highlighted clinician education and the use of clinical support tools as effective strategies to improve AST. Scenario analysis further identified adherence to guidelines and changes in patient-level factors, such as persistence of symptoms and high-risk behaviours, as significant determinants. Both models supported the notion of mandated testing to achieve higher AST initiation rates but with considerations necessary regarding practicality, laboratory constraints, and culture failure rate.

CONCLUSION

The study fundamentally demonstrates a novel approach to conceptualising the patient-clinician dynamic within AMR testing utilising a model-based approach. It suggests targeted interventions to educational, support tools, and legislative framework as feasible strategies to improve AST initiation rates. However, the research fundamentally highlights substantial research gaps in the underlying understanding of AMR.

Development and application of Cas13a-based diagnostic assay for Neisseria gonorrhoeae detection and azithromycin resistance identification

BACKGROUND

Gonorrhoea, caused by Neisseria gonorrhoeae, has spread worldwide. Strains resistant to most antibiotics, including ceftriaxone and azithromycin, have emerged to an alarming level. Rapid testing for N. gonorrhoeae and its antimicrobial resistance will therefore contribute to clinical decision making for early diagnosis and rational drug use.

METHODS

A Cas13a-based assay (specific high-sensitivity enzymatic reporter unlocking; SHERLOCK) was developed for N. gonorrhoeae detection (porA gene) and azithromycin resistance identification (A2059G, C2611T). Assays were evaluated for sensitivity with purified dsDNA and specificity with 17 non-gonococcal strains. Performance of SHERLOCK (porA) was compared with Roche Cobas 4800 using 43 urine samples. Identification of azithromycin resistance mutations (A2059G, C2611T) was evaluated using a total of 84 clinical isolates and 18 urine samples. Lateral flow was tested for this assay as a readout tool. Moreover, we directly assayed 27 urethral swabs from patients with urethritis to evaluate their status in terms of N. gonorrhoeae infection and azithromycin resistance.

RESULTS

The SHERLOCK assay was successfully developed with a sensitivity of 10 copies/reaction, except 100 copies/reaction for A2059G, and no cross-reaction with other species. Comparison of the SHERLOCK assay with the Cobas 4800 revealed 100% concordance within 18 positive and 25 negative urine samples. Of the 84 isolates, 21 strains with azithromycin resistance mutations were distinguished and further verified by sequencing and MIC determination. In addition, 62.96% (17/27) strains from swab samples were detected with no mutant strains confirmed by sequencing.

CONCLUSIONS

The SHERLOCK assay for rapid N. gonorrhoeae detection combined with azithromycin resistance testing is a promising method for application in clinical practice.