Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W1, 9-13, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W1/9/2016/
doi:10.5194/isprs-archives-XLII-4-W1-9-2016
 
29 Sep 2016
IDENTIFYING HIGH-RISK POPULATIONS OF TUBERCULOSIS USING ENVIRONMENTAL FACTORS AND GIS BASED MULTI-CRITERIA DECISION MAKING METHOD
A. R. Abdul Rasam1,2, N. M. Shariff1, and J. F. Dony3 1Geography Programme, School of Distance Education, Universiti Sains Malaysia, Penang, Malaysia
2Centre of Studies for Surveying Science and Geomatics, Faculty of Architecture, Planning and Surveying, Universiti Teknologi MARA, Malaysia
3Sabah State Health Department, Ministry of Health, Malaysia
Keywords: GIS Index Model, Spatial MCDM, Risk Map, Shah Alam, Tuberculosis, Environment Abstract. Development of an innovative method to enhance the detection of tuberculosis (TB) in Malaysia is the latest agenda of the Ministry of Health. Therefore, a geographical information system (GIS) based index model is proposed as an alternative method for defining potential high-risk areas of local TB cases at Section U19, Shah Alam. It is adopted a spatial multi-criteria decision making (MCDM) method for ranking environmental risk factors of the disease in a standardised five-score scale. Scale 1 and 5 illustrate the lowest and the highest risk of the TB spread respectively, while scale from 3 to 5 is included as a potential risk level. These standardised scale values are then combined with expert normalised weights (0 to 1) to calculate the overall index values and produce a TB ranked map using a GIS overlay analysis and weighted linear combination. It is discovered that 71.43% of the Section is potential as TB high risk areas particularly at urban and densely populated settings. This predictive result is also reliable with the current real cases in 2015 by 76.00% accuracy. A GIS based MCDM method has demonstrated analytical capabilities in targeting high-risk spots and TB surveillance monitoring system of the country, but the result could be strengthened by applying other uncertainty assessment method.
Conference paper (PDF, 691 KB)


Citation: Abdul Rasam, A. R., Shariff, N. M., and Dony, J. F.: IDENTIFYING HIGH-RISK POPULATIONS OF TUBERCULOSIS USING ENVIRONMENTAL FACTORS AND GIS BASED MULTI-CRITERIA DECISION MAKING METHOD, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W1, 9-13, doi:10.5194/isprs-archives-XLII-4-W1-9-2016, 2016.

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