| Title |
Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam
|
|---|---|
| Published in |
SpringerPlus, July 2016
|
| DOI | 10.1186/s40064-016-2518-5 |
| Pubmed ID | |
| Authors |
Thanh Quang Bui, Hai Minh Pham |
| Abstract |
There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 83 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 24% |
| Student > Bachelor | 10 | 12% |
| Student > Ph. D. Student | 7 | 8% |
| Researcher | 5 | 6% |
| Student > Postgraduate | 5 | 6% |
| Other | 18 | 22% |
| Unknown | 18 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 14% |
| Engineering | 10 | 12% |
| Medicine and Dentistry | 9 | 11% |
| Environmental Science | 6 | 7% |
| Earth and Planetary Sciences | 6 | 7% |
| Other | 15 | 18% |
| Unknown | 25 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 July 2016.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from SpringerPlus
#1,499
of 1,875 outputs
Outputs of similar age
#327,285
of 370,760 outputs
Outputs of similar age from SpringerPlus
#207
of 263 outputs
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