Evidence map›Paper›PMID 41446401›Full record

ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2025

Characterizing approaches used to display antimicrobial resistance data in veterinary and human medicine: a scoping review.

Famke Alberts, Leilani Rocha, Emily He, Sheila Keay, Kurtis Sobkowich, Casey L Cazer, Scott Weese, Theresa Bernardo, Zvonimir Poljak

Abstract read
In one paragraph

Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Famke AlbertsDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0009-0009-9006-5783
Leilani RochaDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0009-0002-4361-6676
Emily HeDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0009-0006-8419-208X
Sheila KeayDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0000-0001-6804-4518
Kurtis SobkowichDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0000-0001-5702-9427
Casey L CazerDepartment of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, NY, USA.ORCID https://orcid.org/0000-0002-2290-1868
Scott WeeseDepartment of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0000-0003-1896-1937
Theresa BernardoDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.
Zvonimir PoljakDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada.ORCID https://orcid.org/0000-0001-8621-3661

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Antimicrobial resistance (AMR) is a complex One Health problem that requires continuous surveillance to minimize the potential hazards. Information must be disseminated promptly in easily understandable formats to support informed decisions and actions by data end-users. One way to address this is through real-time visualizations, such as dashboards, to help key interest-holders understand and monitor AMR. A scoping review was conducted to understand the current body of evidence surrounding real-time AMR visualizations in both veterinary and human health. Methods: Twelve sources were searched for relevant citations. 1763 citations were included in the screening process. Citations were screened for four main criteria: (i) the text had to be a primary research article in English (ii) published between 1990 and 2023, and (iii) it had to discuss the methodology of an AMR display (iv) that was updated at least quarterly. Results: Forty-two publications were identified as relevant. Publication information, information about the data used in the described displays, display information, and user information were charted. Publications were from 25 countries and utilized data from over 40 databases. Various bacterial genera and species were reported; the most common bacterial species were Conclusions: AMR data visualization has been implemented globally and is a critical component of continued AMR surveillance. Displays are often part of a larger surveillance system. A key challenge is designing a visualization for an intended audience and the information then being utilized by that audience.

Identifiers

PMID41446401
PMCPMC12722559

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.