ReviewOne health (Amsterdam, Netherlands)2025
Comprehensive review of One Health systems for emerging infectious disease detection and management.
Review in One health (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Crimean-Congo Hemorrhagic Fever Virus in Africa: Epidemiological Trends, Transmission Ecology, Hotspot Heterogeneity, and Preparedness Challenges-A Narrative Review.Tropical medicine and infectious disease · 2026Review
- Why One Health struggles: A critical analysis.One health (Amsterdam, Netherlands) · 2026Article
- Challenges and potential opportunities for improving One Health surveillance in low-resource settings: Insights from rabies surveillance in Malawi.One health outlook · 2026Article
- Converging infectious disease threats in the post-COVID era: surveillance fragility, pandemic risk, and global preparedness.Frontiers in public health · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This systematic review investigates how One Health systems, integrated digital platforms combining human, animal, and environmental health data, are currently designed and implemented for infectious disease detection and management. The study aims to identify integration patterns, functional purposes, and user interactivity across 202 reviewed systems published between 2015 and 2024. It categorized these systems by their purpose, diseases addressed, data types (human, animal, environmental), and user groups, such as public health officials and researchers. The tasks performed include data collection, analysis, visualization, and decision-making. Interactive techniques range from interactive filtering to predictive modeling, with varying levels of user interactivity, and note whether functional systems are available online. The search strategy utilized the keywords "one health dashboard visualization system OR one health dashboard OR one health system" across various databases Including IEEE xplore ScienceDirect PubMed And google scholar As well as other sources. While a significant portion of studies still rely on single-domain data, i.e., 20% of studies use only human data, 12% use only animal data, and 10% use only environmental data. The largest group (30%) integrates human and animal data, followed by 12% combining human and environmental data, and a smaller portion (1%) integrating animal and environmental data. The details of this comprehensive survey can be found on this webpage: https://onlylinks.cc/DjHH. There is a clear trend toward integrating multiple datasets, especially Human and Animal data. However, fully integrated One Health systems that combine all three domains remain relatively limited and often take the form of commentaries rather than applied systems, highlighting an opportunity for more comprehensive, data-driven implementations in future research.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.