Development of a web-geographical information system application for plotting tuberculosis cases
Open Access
- 19 October 2021
- journal article
- research article
- Published by PAGEPress Publications in Geospatial Health
- Vol. 16 (2)
- https://doi.org/10.4081/gh.2021.980
Abstract
In the last few decades, public health surveillance has increasingly applied statistical methods to analyze the spatial disease distributions. Nevertheless, contact tracing and follow up control measures for tuberculosis (TB) patients remain challenging because public health officers often lack the programming skills needed to utilize the software appropriately. This study aimed to develop a more user-friendly application by applying the CodeIgniter framework for server development, ArcGIS JavaScript for data display and a web application based on JavaScript and Hypertext Preprocessor to build the server’s interface, while a webGIS technology was used for mapping. The performance of this approach was tested based on 3325 TB cases and their sociodemographic data, such as age, gender, race, nationality, country of origin, educational level, employment status, health care worker status, income status, residency status, and smoking status between 1st January 2013 and 31st December 2017 in Gombak, Selangor, Malaysia. These data were collected from the Gombak District Health Office and Rawang Health Clinic. Latitude and longitude of the location for each case was geocoded by uploading spatial data using Google Earth and the main output was an interactive map displaying location of each case. Filters are available for the selection of the various sociodemographic factors of interest. The application developed should assist public health experts to utilize spatial data for the surveillance purposes comprehensively as well as for the drafting of regulations aimed at to reducing mortality and morbidity and thus minimizing the public health impact of the disease.Keywords
This publication has 29 references indexed in Scilit:
- A Model to Forecast Methane Emissions from Topical and Subtropical Reservoirs on the Basis of Artificial Neural NetworksWater, 2020
- Colorectal cancer risk factors in north-eastern Iran: A retrospective cross-sectional study based on geographical information systems, spatial autocorrelation and regression analysisGeospatial Health, 2019
- Investigating the effect of education on knowledge and practice in preventing tuberculosis in eastern IranInternational Journal of Health Promotion and Education, 2019
- World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regionsThe Lancet. Global Health, 2019
- Demographic, socio-economic and behavior as risk factors of tuberculosis in Malaysia: a systematic review of the literatureReviews on Environmental Health, 2018
- Access to dialysis services: A systematic mapping review based on geographical information systemsGeospatial Health, 2018
- SpatialEpiApp : A Shiny web application for the analysis of spatial and spatio-temporal disease dataSpatial and Spatio-temporal Epidemiology, 2017
- Analisis Perubahan Guna Tanah dan Litupan Bumi di Gombak, Selangor Menggunakan Data Penderiaan JauhSains Malaysiana, 2016
- DotMapper: an open source tool for creating interactive disease point mapsBMC Infectious Diseases, 2016
- Performance Analysis Framework Codeigniter and CakePHP in Website CreationInternational Journal of Computer Applications, 2014