Antibiotic resistance in aquatic environments: priorities and knowledge for water quality modelling [Abstract only] - Jampani, Mahesh; Mateo-Sagasta, Javier; Langan, Simon J. (2023)
Antibiotics have revolutionized medicine and enabled the prevention of bacterial infections that were previously deemed untreatable. In parallel, bacteria have increasingly developed resistance because of the overuse and misuse of antibiotics; as a result, antibiotic resistance (AR) has become a major public health public health concern in recent years. When resistant bacteria find their way into aquatic environments, animal and human exposures to resistant pathogens increase, and health risks multiply. Aquatic environments play a crucial role in AR development and spread where they receive antibiotics, antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) from a number of sources such as agriculture, aquaculture, and wastewater treatment plants. Water quality modelling is an increasingly important approach to understanding AR in aquatic environments; it can help identify resistance patterns of emerging concern, evaluate fate and transport, assess infection risks, and look into their management. However, research on modelling AR in aquatic environments is still in its early stages. The conceptual understanding of sources and pathways of antibiotics, ARB, and ARGs from society to the water systems is essential for setting the scene and developing an appropriate modelling framework. The factors and processes associated with climate change, hydrology and ecology can significantly affect the fate and transport of ARB and ARGs in natural environments. This paper discusses current knowledge, research gaps, and priorities for developing water quality models to assess the fate and transport of ARB and ARGs. Further, we provide a conceptual water quality modelling framework through a critical review of methods and approaches. Prioritizing the development of fate and transport models for AR could provide insights into bacterial evolution and help manage environmental pollution and mitigate health risks. Developing different modelling scenarios and management strategies based on the proposed framework could improve health and water security and therefore achieve Sustainable Development Goals 3 and 6.