Literature DB >> 14554138

Automated graphic image generation system for effective representation of infectious disease surveillance data.

Masashi Inoue1, Shinsaku Hasegawa, Akihiko Suyama, Shunsuke Meshitsuka.   

Abstract

Infectious disease surveillance schemes have been established to detect infectious disease outbreak in the early stages, to identify the causative viral strains, and to rapidly assess related morbidity and mortality. To make a scheme function well, two things are required. Firstly, it must have sufficient sensitivity and be timely to guarantee as short a delay as possible from collection to redistribution of information. Secondly, it must provide a good representation of the results of the surveillance. To do this, we have developed a database system that can redistribute the information via the Internet. The feature of this system is to automatically generate the graphic images based on the numerical data stored in the database by using Hypertext Preprocessor (PHP) script and Graphics Drawing (GD) library. It dynamically displays the information as a map or bar chart as well as a numerical impression according to the real time demand of the users. This system will be a useful tool for medical personnel and researchers working on infectious disease problems and will save significant time in the redistribution of information.

Entities:  

Mesh:

Year:  2003        PMID: 14554138     DOI: 10.1016/s0169-2607(02)00129-3

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  Design and prototype of a mechanism for active on-line emerging/notifiable infectious diseases control, tracking and surveillance, based on a national healthcare card system.

Authors:  Jyh-Win Huang; Ting-Wei Hou
Journal:  Comput Methods Programs Biomed       Date:  2007-03-26       Impact factor: 5.428

2.  Online GIS services for mapping and sharing disease information.

Authors:  Sheng Gao; Darka Mioc; Francois Anton; Xiaolun Yi; David J Coleman
Journal:  Int J Health Geogr       Date:  2008-02-25       Impact factor: 3.918

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.