Developing Surrogate Markers for Predicting Antibiotic Resistance “Hot Spots” in Rivers Where Limited Data Are Available
Amelie Ott, Greg O’Donnell, Ngọc Hân Trần, Mohd Ridza Mohd Haniffah, Jian‐Qiang Su, Andrew M. Zealand, Karina Yew‐Hoong Gin, Michaela L. Goodson, Yong‐Guan Zhu, David W. Graham
Abstract
< 0.05). We suspect this results from minimally treated sewage inputs, which also contain AR bacteria and genes, depleting DO in the most impacted reaches. Thus, although DO is not a measure of AR, lower DO levels reflect wastewater inputs, flagging possible AR hot spots. DO measurement is inexpensive, already monitored in many catchments, and exists in many numerical water quality models (e.g., oxygen sag curves). Therefore, we propose combining DO data and prospective modeling to guide local interventions, especially in LMIC rivers with limited data.
Topics & Concepts
Environmental scienceWater qualityFlaggingAntibiotic resistanceDrainage basinHydrology (agriculture)AntibioticsEcologyBiologyMicrobiologyGeographyCartographyEngineeringGeotechnical engineeringPharmaceutical and Antibiotic Environmental ImpactsAntibiotics Pharmacokinetics and EfficacyAntibiotic Use and Resistance