학술논문

An agent-based multi-level model to study the spread of antimicrobial-resistant gonorrhoea
Document Type
Conference
Source
2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Bioinformatics and Biomedicine (BIBM), 2022 IEEE International Conference on. :803-808 Dec, 2022
Subject
Bioengineering
Computing and Processing
Signal Processing and Analysis
Microorganisms
Antibiotics
Biological system modeling
Surveillance
Sociology
Probabilistic logic
Statistics
Epidemics on network
Dynamic multi-layer network
Antimicrobial resistance
Agent-based model
multi-level model
Language
Abstract
Antimicrobial resistance (AMR) is a major public health problem of the 21st century. The ability of some bacteria to develop resistance to specific antibiotics is the cause of an increased morbidity, mortality and health expenditure. Several surveillance programms have been introduced in the last decades to monitor the spread of antimicrobial resistance. The present work has been conducted within the JPIAMR-project MAGIcIAN whose aim is to support the sustainable introduction of novel class and last-resort antimicrobial drugs minimising the emergence of AMR. Within this project we developed a multi-level model to describe the spread of the sexually transmitted disease of gonorrhoea, caused by the Neisseria gonorrhoeae bacterium, a multidrug resistant bacteria who has progressively developed resistance to many treatment options. The multi-level model includes a dynamic sexual contact network, that describes the dynamic of sexual partnerships, a transmission model that describes the probability of infection during intercourse, and a within-host model, that describes the dynamic of gonorrhoea infection within an individual. The novelty of the proposed model is in including communities having different sexual orientations and behaviour and the possibility of these communities to interact in a dynamic framework. In this work, we calibrate the model using data coming from several clinics located in Amsterdam.