Geospatial, cloud and web based model for evidence based decision making in tuberculosis prevention

Abstract

Today, stakeholders in the fight against TB face a dilemma of the quick spreading disease that must be fought with minimal resources. The scarcity of the resources for fighting Tuberculosis (TB) calls for creative and strategic ways to succeed. Information and Communication Technologies (ICTs), such as cloud computing, geospatial data analysis and web technologies presents an opportunity to creatively fight TB. The ability of these ICTs to capture and present spatial data in real-time, on mapping applications makes them a good candidate for exploration in TB prevention. The aim of this study was to develop a decision support model that would help to prevention TB through improved monitoring and tracking using cloud computing, geospatial data and web technologies by providing information upon which TB program managers can base the planning and implementation of impactful TB control and prevention interventions. The study worked to identify and establish factors which escalate the spread of the TB in the Zambian settings by conducting a baseline study in Lusaka district. Results of this study showed crowding, poor ventilation and exposure due proximity to be major drivers of transmission with each of these variables for surveyed participants scoring 86 percent, 68 percent and 56 percent respectively. The next step was to design a model which incorporates cloud technology, geospatial data analysis and web technologies into the TB prevention algorithm currently being used by the Ministry of Health. The model incorporates cloud computing, whose application helps to send the parameters of a particular TB case to the database in the cloud, geospatial data analysis, whose application supports the mapping of areas in communities with TB cases and web technologies used to develop a web application for data capturing and generation of maps and reports upon which stakeholders can base their decisions when planning and implementing TB prevention and control activities. Based on the designed model, the prototype was developed as the output of the research project. The prototype provides information which can be used as opposed to carrying out one-fits-all TB control and prevention activities and interventions. The prototype, for high yielding results, provides information via a map, showing community areas with TB transmission and also summarizes the factors escalating the transmission in those areas so that stakeholders can plan the best prevention and control measures to be carried out in those areas and thus the prototype provides information which enables stakeholders to put the scare resources where it matters more in the fight against TB - where the cases are. The prototype was developed using the cloud computing architecture, Google Mapping API, MySQL and PHP Scripting Language.