Revised simulation model does not predict rebound in gonorrhoea prevalence where core groups are treated in the presence of antimicrobial resistance

Abstract

Objectives: To determine the effects of using discrete versus continuous quantities of people in a compartmental model examining the contribution of antimicrobial resistance (AMR) to rebound in the prevalence of gonorrhoea.

Methods: A previously published transmission model was reconfigured to represent the occurrence of gonorrhoea in discrete persons, rather than allowing fractions of infected individuals during simulations.

Results: In the revised model, prevalence only rebounded under scenarios reproduced from the original paper when AMR occurrence was increased by 10(5) times. In such situations, treatment of high-risk individuals yielded outcomes very similar to those resulting from treatment of low-risk and intermediate-risk individuals. Otherwise, in contrast with the original model, prevalence was the lowest when the high-risk group was treated, supporting the current policy of targeting treatment to high-risk groups.

Conclusions: Simulation models can be highly sensitive to structural features. Small differences in structure and parameters can substantially influence predicted outcomes and policy prescriptions, and must be carefully considered.

Keywords: ANTIBIOTIC RESISTANCE; ANTIMICROBIAL RESISTANCE; GONORRHOEA; MATHEMATICAL MODEL; NEISSERIA GONORRHOEA.