Abstract
Antibiotic use in the healthcare and agriculture sectors has resulted in levels being found in environmental compartments including surface waters. This can create a selective pressure toward antibiotic resistance development, representing a potential risk to human health. Examining the Irish scenario, this screening paper develops a novel risk ranking model to comparatively assess, on a national scale, the predicted amount of antibiotics entering water bodies as a result of their use in healthcare and agricultural sectors, and the subsequent risk of antibiotic resistance development. Probabilistic modelling approaches, based on data sourced from published literature on antibiotics, are used to account for inherent uncertainty and variability in the input factors; usage, metabolism, degradation and wastewater removal rates, estimating the mass of six antibiotic classes released daily from both sectors. These mass estimates are used to generate predicted concentrations and risk quotient values for each drug class, utilising estimated minimum inhibitory concentration values sourced from the literature. Modelled results predict higher risk quotient (RQ) values in the healthcare compared to agriculture sector, with macrolides and penicillins ranking highest in terms of RQ value. A lower RQ is also predicted from human-use tetracyclines, trimethoprim, and quinolones. Avenues for runoff reduction for each antibiotic class, in particular the higher-risk classes, in both usage sectors are discussed. For validation, predicted levels are compared to observed levels of antibiotic residues in Ireland. Key knowledge gaps to assist prediction and modelling of antibiotic pollution in future studies are also discussed. This research paper establishes a protocol and model structure, applicable to other regions, to compare the contributions of healthcare and agriculture to antibiotic pollution, and identifies highest-ranked antibiotic classes in terms of potential resistance development for prioritisation in the Irish situation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have