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Visualization and analytics tools for infectious disease epidemiology: a systematic review.
Lauren N Carroll1, Alan P Au1, Landon Todd Detwiler2
1Department of Biomedical Informatics and Medical Education, University of Washington, 850 Republican St., Box 358047, Seattle, WA 98109, United States.
Journal of Biomedical Informatics
|April 22, 2014
Summary
Public health professionals need user-centered infectious disease visualization tools. Adoption is hindered by usability issues, data concerns, and lack of support, requiring better integration and interoperability.
Area of Science:
- Public Health Informatics
- Infectious Disease Epidemiology
- Data Visualization
Background:
- Numerous tools aid public health professionals in analyzing and visualizing infectious disease data.
- A systematic review was conducted to understand user needs and the landscape of visualization tools, focusing on GIS, molecular epidemiology, and social network analysis.
Purpose of the Study:
- Identify public health user needs and preferences for infectious disease visualization tools.
- Characterize existing tools' architecture and features.
- Identify commonalities in data type approaches.
- Describe usability evaluation efforts and adoption barriers.
Main Methods:
- Systematic literature review of articles published from 1980 to 2013.
- Included articles focused on infectious disease visualization tools, public health user needs, or usability.
Main Results:
- 88 articles met inclusion criteria, revealing diverse user needs and tool functionalities.
- Tool architecture was often poorly described; few included usability studies or dissemination plans.
- Barriers to adoption included data sharing concerns, lack of organizational support, access issues, and misconceptions.
Conclusions:
- User needs, computer literacy, workflow integration, and trust are crucial for tool adoption.
- Interoperability challenges exist due to the interdisciplinary nature of infectious disease control.
- Future work should address uncertainty representation and minimize cognitive overload for users.
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