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TRAPS - A Visual Analytics System for Public Health Surveillance

10 pagesPublished: July 12, 2024

Abstract

This article proposes a visual analytic framework for monitoring and evaluating preven- tive health programs. The Centers for Disease Control and Prevention (CDC) developed an evaluation framework that focuses on a set of guidelines for public health professionals to evaluate public health programs. This article underlines a growing need for a visual analytic framework to support public health professionals with tasks related to managing programmatic activities and helping them monitor and evaluate ongoing efforts to plan for future programs. Visual analytic frameworks are conceptualized to address domain-specific tasks that equip domain experts with analytical reasoning to make better decisions. We present the Tobacco Reporting and Progress System (TRAPS), a visual analytic system used for managing and evaluating tobacco cessation programs in Mississippi. We assessed the TRAPS data portal based on user logs and the program evaluator’s observations uti- lizing the system for evaluating tobacco control programs. The TRAPS data portal could also be used to help monitor and report other preventive public health programs with similar needs.

Keyphrases: health informatics, health information system, preventive health, program evaluation, public health, public health surveillance, tobacco cessation programs, tobacco control, tobacco surveillance, visual analytics

In: Hisham Al-Mubaid, Tamer Aldwairi and Oliver Eulenstein (editors). Proceedings of the 16th International Conference on Bioinformatics and Computational Biology (BICOB-2024), vol 101, pages 83-92.

BibTeX entry
@inproceedings{BICOB-2024:TRAPS_Visual_Analytics_System,
  author    = {Sujan Ranjan Reddy Anreddy and Katerina Sergi and Robert McMillen and Colleen Stouffer and Nell Valentine},
  title     = {TRAPS - A Visual Analytics System for Public Health Surveillance},
  booktitle = {Proceedings of the 16th International Conference on Bioinformatics and Computational Biology (BICOB-2024)},
  editor    = {Hisham Al-Mubaid and Tamer Aldwairi and Oliver Eulenstein},
  series    = {EPiC Series in Computing},
  volume    = {101},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/1kkM},
  doi       = {10.29007/3c5q},
  pages     = {83-92},
  year      = {2024}}
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