Climate risk mapping of dengue and malaria cases in Kuala Lumpur and Selangor, Malaysia

• Main Author: Hassan, Hafiz
• Format: Thesis
• Language: English
• Published: 2013
• Online Access: http://psasir.upm.edu.my/id/eprint/67697/1/FPAS%202013%2018%20IR.pdf; http://psasir.upm.edu.my/id/eprint/67697/
• Institution: Universiti Putra Malaysia

Local health enforcement activities regarding mosquito-borne disease control and eradication seldom takes climate factors into consideration. The objectives of this study are to find out the historical trend of dengue fever (DF) and malaria fever (MF) in Peninsular Malaysia, to find out the spatial relationship between the climate factors and cases of DF and MF in Selangor and Kuala Lumpur and to prove the feasibility of climate factors to be used in predictive risk mapping for dengue and malaria in Selangor and Kuala Lumpur. For objective one, simple choropleth maps are used with secondary data to visualize the trend and change of DF and MF cases from 1980 to 2010 among states in Peninsular Malaysia supplemented with simple correlation analysis with land uses of forest and urban area percentage. The next objective is carried out by using the geospatial analysis of Standard Deviation Ellipse (SDE) and cluster analysis based on the Getis-Ord General G (Gi*) Hotspot Analysis spatial statistics. Lastly, the risk map based on climate factors is formulated through Co-Kriging method which will then be validated against real data. In the initial mapping of Peninsular Malaysia’s DF and MF cases of 1980 to 2010, dengue has a rising trend while malaria decreases with Malaysia’s population and urbanization growth. Statistical analysis has shown positive correlations for urban areas and dengue (r = 0.49), population density and dengue (r = 0.48); and forested areas and malaria (r = 0.74). Next, SDEs visualized the distribution of climate factors against dengue and malaria cases in Selangor and Kuala Lumpur and through overlay, showed that the mean distributions of dengue and malaria cases were situated within the same focal hotspot as the climate factors. The DF, MF, and rainfall values are found to be clustered with z-values of 2.72, 3.64 and 2.77. A risk map was produced using multiple co-kriging method to predict the cases of DF and MF in Selangor and Kuala Lumpur. Validation using scaled choropleth comparisons showed that the risk map’s predicted cases have a difference of 0.2 levels against dengue cases and malaria cases. In conclusion, Peninsular Malaysia’s DF trend is rising while MF is decreasing between 1990 and 2010. The climate factors, which are spatially correlated with the distribution of DF and MF cases, can be used to predict of the distribution of future DF and MF cases in Selangor and Kuala Lumpur.