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Modeling Antimicrobial Resistance Spread in Riverine Ecosystems: A Multidisciplinary Approach
Summary
Researchers developed a multidisciplinary modeling framework to simulate antimicrobial resistance (AMR) spread in riverine ecosystems, incorporating wastewater discharge, agricultural runoff, and microplastic-associated resistance gene transfer. The model predicted AMR gene concentrations along river corridors and identified intervention points for reducing environmental AMR dissemination.
The rise of antimicrobial resistance (AMR) among critical pathogens poses an escalating threat to human, animal, and environmental health.Riverine ecosystems serve as major reservoirs and conduits for the dissemination of AMR due to diverse anthropogenic pressures including wastewater discharge, agricultural runoff, and industrial pollution.This study presents a multidisciplinary modeling framework integrating metagenomic data, chemical contaminant analyses, hydrological simulations, and social-ecological insights to elucidate AMR spread dynamics in riverine environments.The framework incorporates One Health principles, emphasizing the interconnectedness of ecosystem and public health factors.Results reveal significant contributions of ESKAPEE pathogens and co-selective contaminants, such as triclosan and heavy metals, to resistome proliferation.Seasonal hydrological changes modulate the transport of ARGs, and community behaviors influence exposure patterns.The model provides actionable insights for targeted interventions aimed at mitigating AMR risks in aquatic ecosystems, advancing environmental and public health security.
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