ArticleWellcome open research2024
Empowering Global AMR Research Community: Interactive GIS dashboards for AMR data analysis and informed decision-making.
Article in Wellcome open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Using GIS Dashboards to highlight AMR data disparities in Africa for Policy, Research, and Public Health.PloS one · 2026Article
- Comprehensive review of One Health systems for emerging infectious disease detection and management.One health (Amsterdam, Netherlands) · 2025Review
- Veterinarians' Perspectives on the Antimicrobial Resistance (AMR) Dashboard: A Survey of Needs and Preferences to Inform Development.Veterinary sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Background: Antimicrobial Resistance (AMR) poses a global public health challenge, necessitating advanced tools to support data analysis, and visualization. This study introduces interactive Geographic Information System (GIS) dashboards as innovative platforms for AMR data analysis and visualization, offering comprehensive insights into resistance patterns, and geographic distribution across multiple countries, with a specific focus on Africa. Methods: Three GIS dashboards were developed to address key objectives. The first integrates over 860,000 ATLAS data points from 83 countries, providing an interactive platform. Users can filter data by variables such as country, year, and region, enhancing data accessibility and visualization. The second dashboard focuses on the ATLAS dataset for Kenya and Uganda, incorporating detailed variables such as species, sample sources, and resistance phenotypes. The third involves Kampala, Uganda, to fill data gaps, enabling localized analyses through interactive features like geographic mapping and sample breakdowns by year. Results: Sub-Saharan Africa faces three major challenges in handling antimicrobial resistance (AMR) data: limited accessibility for non-technical users, inefficiencies in processing large datasets, and insufficient longitudinal data for analysis. The introduction of interactive dashboards significantly improved AMR data visualization and interpretation across different scales. The global AMR dashboard effectively mapped geographical trends, uncovering critical data gaps, particularly the scarcity of AMR records from Africa. The Kenya and Uganda dashboard revealed key resistance patterns, highlighting the ineffectiveness of Ceftriaxone, Erythromycin, Levofloxacin, and Ampicillin against E. coli isolates. Additionally, the Kampala-specific dashboard, developed using simulated data, demonstrated the potential for localized AMR visualization, providing valuable insights where real-world data is limited. Across all platforms, the dashboards' interactive features enhanced data accessibility and streamlined trend identification, making AMR insights more interpretable, especially for researchers in Sub-Saharan Africa. Conclusions: Interactive GIS dashboards enhance AMR data analysis in Sub-Saharan Africa by improving accessibility, efficiently handling large datasets, and addressing data gaps. Unlike spreadsheets such as Excel, which struggle with large datasets due to computer constraints, dashboards offer dynamic visualization, real-time updates, and intuitive data exploration.
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Registered trials
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.