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A Cross-Platform System Architecture for Form Design and Data Analytics for Public Health

Published: 20 August 2017 Publication History

Abstract

The CDC's Epi-Info is widely-used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks. As it exists today, Epi-Info runs only on the Windows platform and is made of separate code-bases for several different devices and use-cases. Software portability has become increasingly important over the past few years. In this poster, we present a cross-platform architecture for Epi-Info. To simplify and expedite future development, the cross-platform system architecture uses Electron, AngularJS, and Python with the capability of running on virtually any desktop or laptop computer. Additionally, the code can be easily deployed to the Web, and has the potential to be a viable solution for several mobile use-cases.

References

[1]
Epi-Info, https://www.cdc.gov/epiinfo/index.html
[2]
Electron, https://github.com/electron/electron
[3]
AngularJS, https://angularjs.org/

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  1. A Cross-Platform System Architecture for Form Design and Data Analytics for Public Health

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      cover image ACM Conferences
      ACM-BCB '17: Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics
      August 2017
      800 pages
      ISBN:9781450347228
      DOI:10.1145/3107411
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 20 August 2017

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      Author Tags

      1. cross-platform
      2. epi-info
      3. public health

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      ACM-BCB '17 Paper Acceptance Rate 42 of 132 submissions, 32%;
      Overall Acceptance Rate 254 of 885 submissions, 29%

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