Watershed condition shapes environmental AMR exposure in Fiji: implications for One Health prevention — The Association Specialists
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  2. Oral Presentations - Communicable disease epidemiology and action
  3. Watershed condition shapes environmental AMR exposure in Fiji: implications for One Health prevention

Watershed condition shapes environmental AMR exposure in Fiji: implications for One Health prevention (23765)

Alice Latinne 1 , Samuel Bloomfield 2 , Alison Mather 2 , Gemma Langridge 2 , Lisa Crossman 2 , John Wain 2 , Serge Morand 3 , Christopher Uzzell 4 , Ponipate Baleinamau 5 , Akanisi Caginitoba 1 , Maria Lalamacuata 5 , Waisea Naisilisili 1 , Kelera Naivalu 5 , Timoci Naivalulevu 5 , Vilisi Naivalulevu 5 , Ingrid Qauqau 1 , Andrew Tukana 1 , Mereia Ravoka 1 , Stacy Jupiter 1 , Jacqueline Thomas 4 , Aaron Jenkins 4
  1. Wildlife Conservation Society, Suva, REWA, Fiji
  2. Quadram Institute Bioscience, Norwich, United Kingdom
  3. Kasetsart University, Bangkok, Thailand
  4. University of Sydney, Sydney, Australia
  5. Fiji National University, Suva, Fiji

Background:
Antimicrobial resistance (AMR) is an emerging public health concern in Pacific Island countries, where environmental pathways may contribute to community exposure. Surveillance remains largely clinical, despite many communities relying on untreated surface waters. Understanding how watershed condition influences environmental AMR is important for identifying exposure pathways and informing upstream prevention within a One Health framework.

Methods:
We conducted a cross-sectional environmental study across 29 communities in five Fijian watersheds spanning gradients of land use and waterborne disease burden. Water, sediment and sanitation swab samples (n=296) were collected and sequenced (Illumina MiSeq) to characterise antimicrobial resistance genes (ARGs). Associations between ARG richness and composition and environmental factors (land use, livestock density, human population and water quality) were analysed using generalized linear models and distance-based redundancy analysis.

Results:
ARG richness varied 2.4-fold across watersheds, indicating marked spatial heterogeneity in environmental AMR exposure. Sanitation swabs showed the highest richness, followed by water and sediments. Watershed land use strongly influenced AMR patterns. In aquatic environments, ARG richness increased with both forest cover and livestock density, while composition followed a gradient from forested to livestock-influenced catchments. Forested watersheds showed ARG profiles consistent with environmental background resistomes, whereas livestock-influenced waters were enriched in resistance genes linked to human and animal antibiotic use. In sediments, ARG patterns were associated with plantation cover and recent deforestation, suggesting a disturbance gradient linked to agricultural intensification.

Conclusion:
Watershed condition shapes environmental AMR patterns in Fiji, influencing potential exposure pathways for communities relying on surface waters. Integrating environmental data into AMR monitoring can strengthen prevention strategies. Nature-based approaches, including forest protection and sustainable land management, offer upstream, climate-resilient interventions to reduce AMR exposure within One Health frameworks in Pacific Island settings.