SynthesisJournal of biomedical informatics2014
Visualization and analytics tools for infectious disease epidemiology: a systematic review.
Synthesis in Journal of biomedical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 5 of them syntheses that pooled 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.
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
89 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Visual communication of public health data: a scoping review.Frontiers in digital health · 2025Pooled it
- Innovating health prevention models in detecting infectious disease outbreaks through social media data: an umbrella review of the evidence.Frontiers in public health · 2024Pooled it
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Electronic data collection, management and analysis tools used for outbreak response in low- and middle-income countries: a systematic review and stakeholder survey.BMC public health · 2021Pooled it
- A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks.International journal of health geographics · 2018Pooled it
- Strategies to support implementation of infectious disease decision support systems: a scoping review.BMC medical informatics and decision making · 2026Article
- Limited education and training, and practical application but high potential demand of spatial epidemiology among public health postgraduates in China: a serial national cross-sectional study.BMC medical education · 2026Article
- Spatiotemporal dynamics of waterborne and foodborne disease outbreaks in Brazil: regional inequality analysis and risk area mapping to inform public health strategies.BMC public health · 2026Article
- Respiratory virology dashboards for primary care and public health insight in England.PloS one · 2026Article
- Web-Based Dashboard for Tracking Cryptococcosis-Related Deaths in Brazil (2000-2022).Tropical medicine and infectious disease · 2025Article
- A Flurry of Infectious Disease Modeling Tools During the COVID-19 Pandemic, Considerations for Future Selection.Pathogens (Basel, Switzerland) · 2025Review
- Evaluating the usability of public health data dashboards as information sources for professionals and the public: Findings from a case study with domain experts.Health information and libraries journal · 2025Article
- Design, Application, and Actionability of US Public Health Data Dashboards: Scoping Review.Journal of medical Internet research · 2025Article
- Epidemiological characteristics and spatiotemporal distribution of hepatitis C in southeast coastal areas of China from 2015 to 2022.BMC infectious diseases · 2025Article
- The mChoice App, an mHealth Tool for the Monitoring of Preexposure Prophylaxis Adherence and Sexual Behaviors in Young Men Who Have Sex With Men: Usability Evaluation.JMIR human factors · 2025Article
- Visualizing multilayer spatiotemporal epidemiological data with animated geocircles.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Advancing Public Health Surveillance in Child Care Centers: Stakeholder-Informed Redesign and User Satisfaction Evaluation of the MCRISP Network.JMIR public health and surveillance · 2024Article
- Epidemiological Characteristics and Spatiotemporal Clustering of Pulmonary Tuberculosis Among Students in Southwest China From 2016 to 2022: Analysis of Population-Based Surveillance Data.JMIR public health and surveillance · 2024Article
- Network development in workplace health promotion - empirically based insights from a cross-company network promoting physical activity in Germany.BMC public health · 2024Article
- The Solutions in Health Analytics for Rural Equity Across the Northwest (SHARE-NW) Dashboard for Health Equity in Rural Public Health: Usability Evaluation.JMIR human factors · 2024Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundA myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools.
methodsWe identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review.
resultsA total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. DISCUSSION AND
conclusionAs the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload.
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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.