Antibiotic resistance in aquatic environments: priorities and knowledge for water quality modelling

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cg.contributor.affiliationInternational Water Management Instituteen
cg.contributor.donorCGIAR Trust Funden
cg.contributor.initiativeOne Health
cg.creator.identifierMahesh Jampani: 0000-0002-8925-719Xen
cg.creator.identifierJavier Mateo-Sagasta: 0000-0003-4526-0140en
cg.creator.identifierSimon Langan: 0000-0003-0742-3658en
cg.identifier.urlhttps://iwra.org/proceedings/congress/resource/IWRA3rdOCJan2023_PPTSess093Jampani.pdfen
dc.contributor.authorJampani, Maheshen
dc.contributor.authorMateo-Sagasta, Javieren
dc.contributor.authorLangan, Simon J.en
dc.date.accessioned2023-12-11T05:37:33Zen
dc.date.available2023-12-11T05:37:33Zen
dc.identifier.urihttps://hdl.handle.net/10568/135169
dc.titleAntibiotic resistance in aquatic environments: priorities and knowledge for water quality modellingen
dcterms.abstractDespite urgent global warnings, antimicrobial resistance (AMR) continues to escalate, with projections of 10 million deaths annually by 2050 if unchecked. In response, the International Water Management Institute (IWMI) and partners highlight the environmental dimensions of AMR, particularly the role of aquatic systems in the transmission of antibiotic-resistant bacteria and genes. While AMR has been largely addressed through strategies to curb antibiotic use, this publication emphasizes the critical need to model the environmental pathways of resistance. IWMI’s proposed source-to-receptor water quality modelling framework captures the fate and transport of antimicrobial contaminants through complex water systems, enabling scenario planning and policy guidance. Drawing on field experiences and interdisciplinary research, the framework aims to inform regulatory responses, investment in treatment technologies, and sustainable waste management. The report identifies gaps in environmental data and model calibration, calling for coordinated action across research, institutions, and governments to build resilient, data-driven systems that mitigate the spread of AMR and protect water resources and public health.en_US
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationJampani, Mahesh; Mateo-Sagasta, Javier; Langan, Simon. 2023. Antibiotic resistance in aquatic environments: priorities and knowledge for water quality modelling. Presented at the UNESCO IWRA 2023 Online Conference - Emerging Pollutants: Protecting Water Quality for the Health of People and the Environment, 17-19 January 2023. 11p.en
dcterms.extent11p.en
dcterms.issued2023-01-19en
dcterms.languageen
dcterms.licenseOther
dcterms.subjectresistance to antibioticsen
dcterms.subjectaquatic environmenten
dcterms.subjectwater qualityen
dcterms.subjectmodellingen
dcterms.subjectbacteriaen
dcterms.subjectpollutionen
dcterms.subjecttransformationen
dcterms.subjectwastewateren
dcterms.subjecthealth hazardsen
dcterms.typePresentation

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