Approaching multi-dimensional cube for visualization-based epidemic warning system - dengue fever

  • Authors:

  • Phuoc Vinh Tran;Hong Thi Nguyen;Trung Vinh Tran

  • Affiliations:

  • University of Information Technology Linhtrung, Thuduc, Hochiminh City, Vietnam;University of Information Technology Linhtrung, Thuduc, Hochiminh City, Vietnam;University of Oklahoma, Norman, Oklahoma

  • Venue:
  • Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
  • Year:
  • 2014

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Abstract

Some infectious diseases such as dengue fever, flu, cholera, SARS, AIDS, and so on have been threatening human life because they not only kill many persons at a certain place, but also can spread to many different places. It is necessary to monitor the course of diseases and find a way reducing losses. In this paper, a visualization-based warning system is proposed to control the development of epidemic. The system assists specialists in viewing comprehension, contributing their knowledge as well as experience to the process of extracting information, and estimating the possibility of epidemical outbreaking. Viewing graphics representing data, epidemiologists could estimate the epidemical situation to launch warning message and/or propose a solution preventing epidemical outbreaking on the basis of their available knowledge and experience. The approach of a multi-dimensional cube is utilized in this paper to visualize data relating dengue fever, including the number of infected persons, air temperature, air humidity, and maps of damp mud pools. A multi-dimensional cube is built on the basis of a space-time cube, where data of location are represented on 2-dimensional coordinates as a geographic map of the study area, another dimension indicates time, while the number of patients, temperature, and humidity are represented as comprehensive temporal graphs on private 2-dimensional coordinate systems that are combined with the equivalent locations on the geographic map and shared the time axis with the space-time cube. In addition, thematic maps of damp mud with respect to time are integrated perpendicularly to the time axis of the multi-dimensional cube at corresponding times. With the method of viewing comprehension on multi-dimensional cube of visualization-based warning system, specialists' knowledge and experience are utilized thoroughly in confirming the factors causing disease, keeping track of the course of epidemic, estimating the possibility of outbreaking, and finding out the solution preventing an outbreaking.