Linking environmental antimicrobial resistance to human acquisition: evidence, knowledge gaps and a mechanistic framework
- 1Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France
Abstract
The contribution of environmental reservoirs to antimicrobial resistance (AMR) acquisition in humans remains poorly quantified, despite extensive evidence that resistant bacteria and resistance genes circulate through wastewater, surface waters, food and other environmental matrices. The central difficulty is no longer to demonstrate that these reservoirs are connected, but to quantify the direction and relative contribution of the pathways linking environmental AMR to human acquisition. Here, we synthesize the main processes that need to be represented at the environment-human interface and propose a mechanistic framework for extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-Ec) linking human, water and food compartments.
The framework explicitly represents human-to-environment contamination and multiple environment-to-human exposure routes, including drinking water, recreational water exposure and irrigation-mediated food contamination. We apply the model to two contrasting illustrative settings, France and Madagascar, and use antibiotic-use, environmental-contamination and climate-related scenarios to explore how changes in specific drivers propagate across compartments. The simulations show strongly compartment-dependent responses, while sensitivity analyses identify wastewater treatment efficiency and interface-specific transmission, exposure and environmental-selection parameters as influential components of the system.
The framework is used to explore how different transmission pathways and environmental drivers can shape AMR dynamics across interconnected human and environmental compartments. By comparing contrasting scenarios and identifying the parameters that most strongly influence model behaviour, we highlight both potential leverage points and critical gaps in current empirical knowledge. More broadly, this work illustrates how decomposing One Health AMR into tractable reservoir interfaces can help structure future data collection and progressively improve our ability to quantify transmission between reservoirs.
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/26365397v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): [email protected]@87e9bforg.highwire.dtl.DTLVardef@1033450org.highwire.dtl.DTLVardef@15fa713_HPS_FORMAT_FIGEXP M_FIG C_FIG
Related
- Rethinking Ayurvedic antibacterials: a mechanistic case for multi-target phytochemicals as adjuvants against antimicrobial resistance
- Knowledge, Attitudes, and Practices Regarding Antimicrobial Resistance Among Users of an Indian Digital Healthcare Platform: A Cross-sectional Online Survey
- Breaking the ERK1/2 negative feedback loop: avoiding reactivation and acquisition of resistance by ERK1/2 to anti-cancer agents
- The Effect of Mobile Micro-Learning on Critical Care Nurses' Knowledge Acquisition, Self-Confidence, Motivation, and Stress toward Cardiopulmonary Resuscitation
- Environmental phthalate and chronic kidney disease: Epidemiology, mechanistic pathways, and clinical implications
BibTeX
@misc{alexa2026linking,
title = {{Linking environmental antimicrobial resistance to human acquisition: evidence, knowledge gaps and a mechanistic framework}},
author = {M. Alexa and E. Hodbert and J. Seurat and M. Opatowski and A. Kovacevic and L. Opatowski and L. Armand-Lefevre and D. Hocquet and E. Buelow},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.13.26365397},
url = {https://www.medrxiv.org/content/10.64898/2026.10.13.26365397v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Linking environmental antimicrobial resistance to human acquisition: evidence, knowledge gaps and a mechanistic framework
AU - M. Alexa
AU - E. Hodbert
AU - J. Seurat
AU - M. Opatowski
AU - A. Kovacevic
AU - L. Opatowski
AU - L. Armand-Lefevre
AU - D. Hocquet
AU - E. Buelow
PY - 2026
DA - 2026/10/13
PB - medRxiv
DO - 10.64898/2026.10.13.26365397
UR - https://www.medrxiv.org/content/10.64898/2026.10.13.26365397v1
AB - The contribution of environmental reservoirs to antimicrobial resistance (AMR) acquisition in humans remains poorly quantified, despite extensive evidence that resistant bacteria and resistance genes circulate through wastewater, surface waters, food and other environmental matrices. The central difficulty is no longer to demonstrate that these reservoirs are connected, but to quantify the direction and relative contribution of the pathways linking environmental AMR to human acquisition. Here, we synthesize the main processes that need to be represented at the environment-human interface and propose a mechanistic framework for extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-Ec) linking human, water and food compartments. The framework explicitly represents human-to-environment contamination and multiple environment-to-human exposure routes, including drinking water, recreational water exposure and irrigation-mediated food contamination. We apply the model to two contrasting illustrative settings, France and Madagascar, and use antibiotic-use, environmental-contamination and climate-related scenarios to explore how changes in specific drivers propagate across compartments. The simulations show strongly compartment-dependent responses, while sensitivity analyses identify wastewater treatment efficiency and interface-specific transmission, exposure and environmental-selection parameters as influential components of the system. The framework is used to explore how different transmission pathways and environmental drivers can shape AMR dynamics across interconnected human and environmental compartments. By comparing contrasting scenarios and identifying the parameters that most strongly influence model behaviour, we highlight both potential leverage points and critical gaps in current empirical knowledge. More broadly, this work illustrates how decomposing One Health AMR into tractable reservoir interfaces can help structure future data collection and progressively improve our ability to quantify transmission between reservoirs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/26365397v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): [email protected]@87e9bforg.highwire.dtl.DTLVardef@1033450org.highwire.dtl.DTLVardef@15fa713_HPS_FORMAT_FIGEXP M_FIG C_FIG
ER -