One Health Alternate Antimicrobial Resistance Monitoring System (AlARMS)

Grant number: 228172/Z/23/Z

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Key facts

  • Disease

    N/A

  • Start & end year

    2023
    2025
  • Known Financial Commitments (USD)

    $269,452.55
  • Funder

    Wellcome Trust
  • Principal Investigator

    Prof Sabiha Y Essack
  • Research Location

    South Africa
  • Lead Research Institution

    University of Kwazulu Natal
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Pathogen genomics, mutations and adaptations

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

Leveraging the existing wastewater surveillance infrastructure built for polio and COVID-19 in South Africa, and, using a metagenomic approach, the proposed Alternate Antimicrobial Resistance Monitoring System (AlARMS) will delineate the burden of AMR from the longitudinal surveillance of the microbiome, resistome and mobilome in multiple One Health settings, comparing and contrasting genomic data from three sources: gut microbiota of vulnerable/at- risk humans, gut microbiota of their major, intensively-produced food animal sources, and associated wastewater microbiota. AlARMS will ascertain whether AMR in wastewater is representative of AMR in the microbiota of vulnerable/at- risk human (adding a step to the sewage-clinical AMR correlation by linking population-level AMR data) and animal populations and compare this to AMR in contemporary bacterial isolates from clinical and veterinary laboratories. The project will additionally explore the correlation/association (if any) between antimicrobial use (AMU) and antimicrobial residues in wastewater. AlARMS also includes an ethnographic study to ascertain socio-behavioural drivers of AMR and uses mathematical modelling to elucidate transmission dynamics. AlARMS may serve as early-warning and a proxy for conventional AMR surveillance systems in humans, food animals and the water, sanitation and hygiene (WASH) sector.