Evidence map›Paper›PMID 41900290›Full record

ReviewMicroorganisms2026

Operationalising Genomic Surveillance for Antimicrobial Resistance in Low- and Middle-Income Countries: A One Health Perspective from Bangladesh.

Khushal Singh, Suparna Mitra

Abstract readReview
In one paragraph

Review in Microorganisms, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Khushal SinghLeeds Institute of Medical Research, St James Campus, University of Leeds, Leeds LS9 7TF, UK.
Suparna MitraLeeds Institute of Medical Research, St James Campus, University of Leeds, Leeds LS9 7TF, UK.ORCID 0000-0002-9378-1496

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) represents a critical global health challenge, with low- and middle-income countries (LMICs) disproportionately affected due to limited surveillance capacity. Advances in microbial genomics offer powerful tools for AMR detection and monitoring; however, translating these technologies into sustainable, policy-relevant surveillance systems in resource-constrained settings remains challenging. This review synthesises current approaches to genomic surveillance of AMR in LMICs and presents Bangladesh as a case study to illustrate how genomic, environmental, and clinical data can be integrated within a One Health framework. We examine key barriers to implementation, including laboratory infrastructure, bioinformatics capacity, data governance, and cross-sector coordination, alongside emerging opportunities for capacity building and regional collaboration. Using Bangladesh as a case study, we highlight practical pathways for embedding genomic surveillance into national AMR strategies, integrating human, animal, and environmental reservoirs of antibiotic resistance. We argue that genomic surveillance can move beyond data generation to inform infection prevention, antibiotic stewardship, and public health decision making when supported by context-appropriate infrastructure and interdisciplinary engagement. By focusing on operational and translational considerations rather than technology alone, this review provides actionable insights for microbiologists, public health practitioners, and policymakers seeking to strengthen AMR surveillance systems in LMICs through a One Health approach.

Indexed as

antimicrobial resistance (AMR)genomic surveillancehealth inequitieslow- and middle-income countries (LMICs)metagenomicsone health

Identifiers

PMID41900290
PMCPMC13029129

What Socratic 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 Socratic graph.