Spatio-Temporal Distribution of Malaria in Perak, Malaysia

Malaria incidence in Perak, Malaysia has generally declined, but there remain regions of high incidence. The spatio-temporal distribution pattern of malaria in Perak was studied using Geographical Information Systems (GIS) and spatial statistical tools. Malaria data cases at the subdistrict level in Perak from 2007 to 2011 were analysed to determine the spatial and temporal distribution patterns of malaria incidence. Geographical Information Systems (GIS) and spatial statistical tools were used to identify spatial correlation in the data and malaria hot-spots. Spatial correlation was tested by using an autocorrelation method called Moran’s I. Hot spot analysis was done using Getis-Ord G*?statistic technique. Malaria incidence rates were categorized into 3 classes to map the spatial distribution. Malaria cases in Perak were geo-spatially clustered. Most of the hot spots locations were in Kenering, Ulu Kinta, Gerik and Kampar sub-districts. The prevalence of malaria among foreigners was noticeably higher than Malaysians. Improved surveillance of foreign workers can prevent outbreaks and identify high risk areas. This study implies that geographic-based mapping and information system are needed for an effective malaria control.

Health Facilities Affected by Flood Simulation to a District in Malaysia

Objective: The Ministry of Health Malaysia is developing a GIS database of health facilities in the country with the main aim to assist in the planning and development of the services, and in allocation of resources. Methodology: Apart from coordinates of the facilities, other digital information such as states and districts boundaries, main road networks and river were obtained from MacGDI, a centre responsible to manage geospatial data infrastructure in Malaysia. In assisting the Ministry of Health in its planning, one of the analyses that were conducted was a flood simulation analysis in a district in a coastal area of Peninsular Malaysia. This was done following a possibility that a tropical storm “Sonamu” would happen in that area. The objective was to identify health facilities that would be affected if a flood were to happen in the district and finally to assist the Ministry of Health in their emergency plan. Data on contour was obtain from a relevant government agency and was also mapped digitally. Results: The results were showing that with one metre depth of flood, more than half of the facilities would be affected and about two third of the facilities would be affected if the flood level rises to 2.5 metres. Conclusion: Application of GIS is very useful for the health sector in planning of facing an environmental related disaster.