Author: Benedek Plosz -
A new £200,000 study – funded by EU’s H2020 – will assess the spread of antimicrobial resistance under dynamic, environmentally representative conditions, leading to the development of new risk modelling tools as means of surveillance.
The project, IDYEA, is being led by University of Bath and also involves University of Exeter, the UK Centre for Ecology & Hydrology (UKCEH) and the Technical University of Denmark.
Protection of the increasingly scarce water resources is one of the largest challenges facing humanity in the 21st century. Urban water resource treatment for hazardous materials, notably, antibiotic residues is important to mitigate the spread of antimicrobial resistance (AMR) in recipient water systems. The spread of AMR in environmental compartments can be a potent threat to biodiversity, and it poses a ticking time-bomb in public health management. Both the developed and the developing countries are in focus, because antibiotic resistance can be induced by poor infection prevention and control as well as the misuse and overuse of vaccines.
Previous studies predominantly assessed AMR spread, for instance, at static antibiotic exposure levels and such shortcomings can considerably hinder the representativeness of experimental observations, thereby limiting our understanding of the challenge.
To manage AMR risk, IDYEA will focus on developing experimental and numerical models of more realistic water environmental conditions – powerful means to assess systems’ dynamics and their impact on AMR spread in biota.
Public health related benefits of our project entail an integrated risk-assessment platform equipped with improved mathematical risk models, AMR monitoring markers. These tools can then be used by practitioners to devise reliable risk-assessment guidelines on AMR spread, and can lead to develop future water treatment technology and discharge quality criteria for utilities.
Dr Benedek Plosz of University of Bath, principal investigator of the IDYEA project, says:
“In-sewage antimicrobial occurrence can potentially vary as a function of drug administration for example, thus triggering insofar not-well understood exposure dynamics.”
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