Disease Mapping and Spatial Landscape Characterization of Tuberculosis Ecology in Malaysia

Abstract

Abstract. This paper analyses the pattern distribution and influential risk factors of tuberculosis (TB) at 47 Sections of Shah Alam, Malaysia using spatial epidemiological (SE) approach. Quantifying environmental risk factors of the disease pattern can be a challenging task due to spatial environmental and transmission process, whereby each area may have its own unique risk factors and dynamics. A conceptual framework of spatial epidemiological data analysis (Pfieffer et al. 2008), and geographical information system (GIS) method (Chang 2011) are mainly adapted in this research method. Disease mapping of the 3-year datasets (2013 to 2015) was created using GIS analysis and satellite remote sensed land used in identifying the clustering areas of TB pattern. Meanwhile, the potential risk factors of TB in the clustering areas were assessed using spatial landscape ecology through site observation.Figure 1 shows the spatial pattern of TB cases in the study area as a random medium, revealing that TB distribution is well distributed in the area. However, there is also some clustering concentration at the northern zone (Section U17 to Section U20) and some in U5 and U13, while in the central zone, the majority cases are concentrated at Section S7, S17, S18, S19 and S24. Section S27 and S28 are also indicated as high-case areas in the southern zone. It is interesting to note that in the recent years (2015), the disease was a little dispersed and scattered to the northern area especially in U13, U10, U15 and U17 due to the new township area, physical development and human mobility (Nava-Aguilera et al., 2011; Prussing et al., 2013). Furthermore, every zone or section may have its own risk factors; hence, there is a need for specific investigation to be conducted in a smaller area.