Geospatial Modelling For Potential High Risk Tuberculosis Areas In Shah Alam, Selangor
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Date
2018-03
Authors
Abdul Rasam, Abdul Rauf
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
Malaysia has a medium burden of tuberculosis (TB) incidence based on
World Health Organization (WHO) indicator, but the current trend of TB cases is
generally increasing. The Ministry of Health (MOH), Malaysia has set up several
guidelines to control the disease, however, the national TB technical report in 2015
highlighted that existing detection methods of TB on the site still need to be
improved to strenghten the current TB control programme. A geospatial model is
proposed in this study to identify potential high-risk areas of TB and targeted risk
population especially for missing cases and undiagnosed people. This study has four
main objectives: i) to examine the spatial pattern and clustering of TB distribution, ii)
to determine the influential risk factors contributing to local TB cases, iii) to develop
a geospatial eopidemic model (GeoEM) for potential high-risk TB areas, and iv) to
validate the model of GeoEM for actual application. Shah Alam in the district of
Petaling is selected as a study area since it has recorded constant TB cases and it also
has a diversity of environment related TB risk factors. GeoEM is innovatively
developed using spatial epidemiology (SE) approach, geographical information
system (GIS), GIS-multicriteria decision making (MCDM) method, logistic
regression and geostatistical method. The overall spatial pattern of TB in Shah Alam
is a slight medium random that exists in certain clustered areas. TB clustering was
concentrated around northern zone, central zone and a few areas around southern
zone. There are 10 main sections from 47 sections which have significant
relationships with the clustering. It comprises section U17, U18, U19, U20, S7, S17,
S18, S20, S27 and S28. These risk areas have similar geographical features as
occurred to the high burden countries worldwide. The results stimulate new attribue
of risk factor and interpretaion on the disease that is scattered towards north-eastern
zone due to the new township development and human mobility.
Description
Keywords
Geospatial modelling for potential high risk , tuberculosis areas in shah alam, Selangor