Evidence map›Paper›PMID 39435404›Full record

ArticleFrontiers in public health2024

Progress made in digitalizing antimicrobial resistance surveillance in a One Health approach in Kenya.

Veronicah M Chuchu, Joseph Njung'e, Bridgit Muasa, Muchira Gathira, Geoffrey Olela, Kinuthia S Bubi, Justus Ashaba, Susan Githii, Romona Ndanyi, Emmanuel Tanui and 4 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

14 authors.

Veronicah M ChuchuFIND, Geneva, Switzerland.
Joseph Njung'eFIND, Geneva, Switzerland.
Bridgit MuasaNational Veterinary Reference Laboratories, Directorate of Veterinary Services, Kabete, Kenya.
Muchira GathiraNational Veterinary Reference Laboratories, Directorate of Veterinary Services, Kabete, Kenya.
Geoffrey OlelaFIND, Geneva, Switzerland.
Kinuthia S BubiFIND, Geneva, Switzerland.
Justus AshabaFIND, Geneva, Switzerland.
Susan GithiiNational Antimicrobial Stewardship Interagency Committee (NASIC), Ministry of Health and the Ministry of Agriculture and Livestock Development, Nairobi, Kenya.
Romona NdanyiNational Veterinary Reference Laboratories, Directorate of Veterinary Services, Kabete, Kenya.
Emmanuel TanuiNational Antimicrobial Stewardship Interagency Committee (NASIC), Ministry of Health and the Ministry of Agriculture and Livestock Development, Nairobi, Kenya.
John Irungu IrunguNational Antimicrobial Stewardship Interagency Committee (NASIC), Ministry of Health and the Ministry of Agriculture and Livestock Development, Nairobi, Kenya.
Allan AzegeleNational Antimicrobial Stewardship Interagency Committee (NASIC), Ministry of Health and the Ministry of Agriculture and Livestock Development, Nairobi, Kenya.
Rigveda KadamFIND, Geneva, Switzerland.
Cecilia FerreyraFIND, Geneva, Switzerland.

Funding

Zoonotic and Emerging Infectious Diseases Training ProgramD43TW011519 · FIC · WASHINGTON STATE UNIVERSITY · PI Walter Godfrey Jaoko, Thumbi Mwangi · 2020 to 2026
$1.2M
FIC NIH HHS D43 TW011519
6 · The paper itself

Abstract

Background: Antimicrobial resistance (AMR) is a major threat to global public health, affecting human and animal health, agriculture, food safety, and the environment. The control of AMR is often challenging, particularly when data are scanty or siloed in individual sectors. To develop evidence-based control policies for AMR, an electronic information system that integrates AMR data from various sectors, in a One Health approach, is critical. Methodology: Acknowledging the interconnectedness of AMR in humans, animals, and the environment and the need to assess the AMR burden using a One Health approach, Kenya's National Antimicrobial Stewardship Interagency Committee (NASIC), with support from FIND, integrated human and animal health AMR data at the national AMR data repository and developed the One Health AMR Surveillance System (OHAMRS). The OHAMRS comprises two core digital components: interoperability middleware for integrating data from various sources and a DHIS2 web portal for the analysis and visualization of AMR surveillance data from the human and animal health sectors. These components are scalable for future inclusion of data from other One Health sectors, e.g., the environment, food/feed, and aquaculture sectors. Results: The OHAMRS has 42 dashboards that facilitate the presentation, interpretation, and dissemination of actionable information relating to AMR, including 17 dashboards for human and animal health priority pathogens and 8 for drug-resistance indicators. The priority pathogen dashboards provide visualization of antimicrobial susceptibility patterns, resistance and susceptibility trends, resistance tables, and geospatial susceptibility maps. Other dashboards include surveillance sites and specimen reports, data completeness, data reconciliation, sample testing workload, a One Health intersectoral dashboard, and other reporting tools for diverse stakeholders. Discussion: Digitalizing AMR surveillance through a One Health lens is pivotal to understand AMR prevalence and patterns across various sectors. The OHAMRS provides comprehensive data analysis and presentation, informing policymaking on AMR control. Digital tools such as the OHAMRS are vital in facilitating the availability of data and actionable information on AMR required to address the AMR crisis in Kenya.

Indexed as

One HealthAnimalsAnti-Bacterial AgentsAntimicrobial StewardshipDrug Resistance, BacterialHumansKenyaPopulation SurveillanceAnti-Bacterial Agentsantimicrobial resistancedigital healthinteroperabilityOne Healthsurveillance

Identifiers

PMID39435404
PMCPMC11491712

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.