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Mapping Risk Areas of Tuberculosis Using Knowledge-Driven GIS Model in Shah Alam, Malaysia

Abdul Rauf Abdul Rasam, Noresah Mohd Shariff, Jiloris F. Dony and Punitha Makeswaran

Pertanika Journal of Tropical Agricultural Science, Volume 25, Issue S, January 2017

Keywords: Disease mapping, knowledge-driven GIS model, spatial MCDM, risk area, tuberculosis

Published on: 28 Jul 2017

Developing a model to map tuberculosis (TB) cases in Malaysia for boosting early detection is vital. A knowledge-driven geographical information system (GIS) modelling is an alternative approach developed for assessing potential risk areas of TB at Section 17, Shah Alam, Selangor. It is a weight-rating score model and spatial multi-criteria decision making (MCDM) method for producing a ranked map based on the index values and risk indicators with a five-score scale. Results showed 34.85% of the study areas are potential TB high risk zones, ranging from medium to very high risk. This is consistent with the findings obtained from overlay comparison with the current cases in 2015.The TB risk map and validation indicated a reasonable match with areas considered as potential TB risk areas, particularly in urban and crowded environments. Thus, a GIS-based MCDM technique can be applied in the national TB screening and monitoring programme.

ISSN 1511-3701

e-ISSN 2231-8542

Article ID

JSSH-S0314-2016

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