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Updated: Oct 13, 2025

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics
Published on: July 19, 2024
A new modelling framework for assessing the relative burden of antimicrobial resistance in aquatic environments
Shin Giek Goh1, Peng Jiang2, Charmaine Ng1
1NUS Environmental Research Institute, National University of Singapore, 117411, Singapore.
Abstract:
The infections caused by antibiotic resistant bacteria (ARB) can lead to higher medical costs, prolonged hospital stays, and increased mortality compared to bacteria that are susceptible to antibiotics. Challenges exist in quantifying the potential risk/burden associated with antimicrobial resistance (AMR) as there is a lack of dose-response models available for pathogens which are resistant to antibiotics, in addition to the fact that very little is known regarding the health risks posed by antibiotic resistant genes (ARG). In this paper, we proposed a new modelling framework to evaluate the relative burden of AMR in natural aquatic environments. With this framework, an AMR burden score for each sample was calculated based on burden coefficients assigned for each ARB and ARG, as well as weighted burdens for the separate ARBs and ARGs components. The method developed in this study was applied to assess the relative burden of AMR in local aquatic environments with different land uses at different seasons. The collected filed data were used to verify the applicability of the proposed relative burden assessment method. Through the established method, the spatial and temporal hotspots of AMR were identified, which could provide useful information to agencies for better control and management of AMR emergence in natural aquatic environments.
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