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Data Visualization, Information Dissemination, and Alerting
Syndromic surveillance systems are critical for public health surveillance because they often provide epidemiologists and public health officials the visual analytics tools and techniques to synthesize information and detect the data anomalies (possible outbreaks) from massive, dynamic, and often am...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498881/ http://dx.doi.org/10.1007/978-1-4419-1278-7_5 |
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author | Chen, Hsinchun Zeng, Daniel Yan, Ping |
author_facet | Chen, Hsinchun Zeng, Daniel Yan, Ping |
author_sort | Chen, Hsinchun |
collection | PubMed |
description | Syndromic surveillance systems are critical for public health surveillance because they often provide epidemiologists and public health officials the visual analytics tools and techniques to synthesize information and detect the data anomalies (possible outbreaks) from massive, dynamic, and often ambiguous surveillance data. Represented visually, the assessments of public health status are better understood and also more effectively communicated for action. The geographic or spatial components of the surveillance data enable the natural application of visualization techniques for computerized assistance for decision making in spatial (and often spatial-temporal) analytics (e.g., clustering detection and resource logistics). In addition, the interplay between simulation and visualization provides a powerful combination. Visualization techniques can be used to analyze simulation output and analysis results, and can drastically improve the understandability and accessibility of the model to both technical and nontechnical audiences. Virtually all simulation software packages have some level of visualization, ranging from basic diagrams to full animation. This chapter provides a systematic summarization of data visualization techniques that are employed in the surveyed syndromic surveillance systems. Taxonomy of the visualization techniques procedes the discussion of the two classes of visualization technologies: visual information display and interactive visual data exploration. A number of example screenshots from the surveyed syndromic surveillance systems visualizations are shown along with the text. |
format | Online Article Text |
id | pubmed-7498881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
record_format | MEDLINE/PubMed |
spelling | pubmed-74988812020-09-18 Data Visualization, Information Dissemination, and Alerting Chen, Hsinchun Zeng, Daniel Yan, Ping Infectious Disease Informatics Article Syndromic surveillance systems are critical for public health surveillance because they often provide epidemiologists and public health officials the visual analytics tools and techniques to synthesize information and detect the data anomalies (possible outbreaks) from massive, dynamic, and often ambiguous surveillance data. Represented visually, the assessments of public health status are better understood and also more effectively communicated for action. The geographic or spatial components of the surveillance data enable the natural application of visualization techniques for computerized assistance for decision making in spatial (and often spatial-temporal) analytics (e.g., clustering detection and resource logistics). In addition, the interplay between simulation and visualization provides a powerful combination. Visualization techniques can be used to analyze simulation output and analysis results, and can drastically improve the understandability and accessibility of the model to both technical and nontechnical audiences. Virtually all simulation software packages have some level of visualization, ranging from basic diagrams to full animation. This chapter provides a systematic summarization of data visualization techniques that are employed in the surveyed syndromic surveillance systems. Taxonomy of the visualization techniques procedes the discussion of the two classes of visualization technologies: visual information display and interactive visual data exploration. A number of example screenshots from the surveyed syndromic surveillance systems visualizations are shown along with the text. 2009-07-14 /pmc/articles/PMC7498881/ http://dx.doi.org/10.1007/978-1-4419-1278-7_5 Text en © Springer Science+Business Media, LLC 2010 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chen, Hsinchun Zeng, Daniel Yan, Ping Data Visualization, Information Dissemination, and Alerting |
title | Data Visualization, Information Dissemination, and Alerting |
title_full | Data Visualization, Information Dissemination, and Alerting |
title_fullStr | Data Visualization, Information Dissemination, and Alerting |
title_full_unstemmed | Data Visualization, Information Dissemination, and Alerting |
title_short | Data Visualization, Information Dissemination, and Alerting |
title_sort | data visualization, information dissemination, and alerting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498881/ http://dx.doi.org/10.1007/978-1-4419-1278-7_5 |
work_keys_str_mv | AT chenhsinchun datavisualizationinformationdisseminationandalerting AT zengdaniel datavisualizationinformationdisseminationandalerting AT yanping datavisualizationinformationdisseminationandalerting |