Version 1
: Received: 12 October 2023 / Approved: 12 October 2023 / Online: 12 October 2023 (11:24:24 CEST)
Version 2
: Received: 16 May 2024 / Approved: 16 May 2024 / Online: 17 May 2024 (08:01:19 CEST)
Version 3
: Received: 20 September 2024 / Approved: 23 September 2024 / Online: 23 September 2024 (08:49:36 CEST)
How to cite:
Prakhova, S. Evaluating Efficiency of the US Surveillance Systems for Monitoring Antimicrobial-Resistant Gonorrhea: An Agent-Based Modelling Study. Preprints2023, 2023100814. https://doi.org/10.20944/preprints202310.0814.v1
Prakhova, S. Evaluating Efficiency of the US Surveillance Systems for Monitoring Antimicrobial-Resistant Gonorrhea: An Agent-Based Modelling Study. Preprints 2023, 2023100814. https://doi.org/10.20944/preprints202310.0814.v1
Prakhova, S. Evaluating Efficiency of the US Surveillance Systems for Monitoring Antimicrobial-Resistant Gonorrhea: An Agent-Based Modelling Study. Preprints2023, 2023100814. https://doi.org/10.20944/preprints202310.0814.v1
APA Style
Prakhova, S. (2023). Evaluating Efficiency of the US Surveillance Systems for Monitoring Antimicrobial-Resistant Gonorrhea: An Agent-Based Modelling Study. Preprints. https://doi.org/10.20944/preprints202310.0814.v1
Chicago/Turabian Style
Prakhova, S. 2023 "Evaluating Efficiency of the US Surveillance Systems for Monitoring Antimicrobial-Resistant Gonorrhea: An Agent-Based Modelling Study" Preprints. https://doi.org/10.20944/preprints202310.0814.v1
Abstract
We aim to evaluate efficiency of two American surveillance systems for monitoring the spread of antimicrobial-resistant (AMR) gonorrhea among men who have sex with men (MSM) using the novel continuous-time agent-based model of gonorrhea transmission. The model was developed using the simulation modelling tool AnyLogic and accounts for susceptible and resistant strains of N. gonorrhoeae, symptomatic and asymptomatic infection and various routes of transmission between different anatomical sites. The model was calibrated using a Bayesian calibration approach. The surveillance systems are the Gonococcal Isolate Surveillance Project (GISP) and the enhanced Gonococcal Isolate Surveillance Project (eGISP). We calculated accuracy, sensitivity, specificity and estimation error for each surveillance system based on the number of isolates submitted in 2018. We also varied that number to see its effect on the outcomes. Our results show that the accuracy of eGISP was between 66% and 92%, while GISP demonstrates low accuracy between 44% and 48%. We also determined that increasing the number of isolates results in improved performance for eGISP, while GISP is not particularly sensitive to it.
Keywords
Agent-based modelling; antimicrobial-resistant gonorrhea; surveillance systems
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.