Evidence map›Paper›PMID 41284650›Full record

ArticlePLOS global public health2025

Monitoring antimicrobial resistance trends from global genomics data: amr.watch.

Sophia David, Julio Diaz Caballero, Natacha Couto, Khalil Abudahab, Nabil-Fareed Alikhan, Corin Yeats, Anthony Underwood, Alison Molloy, Diana Connor, Heather M Shane and 11 more

Abstract read
In one paragraph

Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Phylogenomic and comparative genomic analyses ofFrontiers in microbiology · 2026
    Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Sophia DavidCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0002-0115-0954
Julio Diaz CaballeroCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Natacha CoutoCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Khalil AbudahabCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Nabil-Fareed AlikhanCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Corin YeatsCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0003-0080-6242
Anthony UnderwoodCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Alison MolloyAlimolloy.com, London, United Kingdom.ORCID https://orcid.org/0009-0001-5433-0844
Diana ConnorCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Heather M ShaneCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Philip M AshtonCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
Hajo GrundmannInstitute for Infection Prevention and Hospital Epidemiology, Medical Centre - University of Freiburg, Freiburg, Germany.ORCID https://orcid.org/0000-0002-9971-522X
Matthew T G HoldenSchool of Medicine, University of St Andrews, St Andrews, United Kingdom.
Edward J FeilThe Milner Centre for Evolution, Department of Life Sciences, University of Bath, Bath, United Kingdom.
Sonia B SiaAntimicrobial Resistance Surveillance Reference Laboratory, Research Institute for Tropical Medicine, Department of Health, Muntinlupa, Philippines.ORCID https://orcid.org/0009-0005-2475-9577
Pilar Donado-GodoyGlobal Health Research Unit for the Genomic Surveillance of Antimicrobial Resistance, CI Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA), Mosquera, Colombia.
Ravikumar K LingegowdaCentral Research Laboratory, KIMS, Bengaluru, India.
Iruka N OkekeDepartment of Pharmaceutical Microbiology, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria.ORCID https://orcid.org/0000-0002-1694-7587
Silvia ArgimónCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.
David M AanensenCentre for Genomic Pathogen Surveillance, Pandemic Sciences Institute, University of Oxford, Oxford, United Kingdom.ORCID https://orcid.org/0000-0001-6688-0854
NIHR Global Health Research Unit on Genomics and enabling data for the Surveillance of AMR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whole genome sequencing (WGS) is increasingly supporting routine pathogen surveillance at local and national levels, providing comparable data that can inform on the emergence and spread of antimicrobial resistance (AMR) globally. However, the potential for shared WGS data to guide interventions around AMR remains under-exploited, in part due to challenges in collating and transforming the growing volumes of data into timely insights. We present an interactive platform, amr.watch (https://amr.watch), that enables interrogation of AMR trends from public WGS data on an ongoing basis to support research and policy. The amr.watch platform incorporates, analyses and visualises high-quality WGS data from WHO-defined priority bacterial pathogens. Analytics are performed using community-standard methods with bespoke species-specific curation of AMR mechanisms. By 31 March 2025, the platform included data from 620,700 pathogen genomes with geotemporal information, with highly variable representation of different species and geographic regions. By integrating WGS data with sampling information, amr.watch enables users to assess geotemporal trends among genotypic variants (e.g., sequence types) and AMR mechanisms, with implications for interventions including antimicrobial prescribing and drug and vaccine development. While metadata inconsistencies demand future attention we focus on the collation of high quality genomic data allied with geotemporal distribution. In conclusion, amr.watch is an information platform for scientists and policy-makers delivering ongoing situational awareness of AMR trends from genomic data. As broad adoption of WGS continues, and crucially, metadata and associated sampling becomes increasingly representative, amr.watch is positioned to monitor both pathogen populations and our global efforts in genomic surveillance, guiding control strategies tailored to each pathogen's characteristics.

Identifiers

PMID41284650
PMCPMC12643278

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.