Abstract
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.
Highlights
Malaria is one of the most deadly vector-borne diseases in the world
Data associated with microscopically confirmed malaria cases between 2002 and 2011 was obtained from the Perak State Health Department to analyze the dynamics of malaria incidence
Malaria cases in Perak showed an overall decline over the past decade except a noticeable increase in 2007 (Figure 2)
Summary
Malaria is one of the most deadly vector-borne diseases in the world. While malaria rates are declining worldwide, there remain geographic regions where incidence rates remain high. (2015) Spatio-Temporal Distribution of Malaria in Perak, Malaysia. Malaysia is currently moving towards malaria elimination [1] and control of malaria outbreaks in high risk areas is the key to achieve this goal. Since malaria incidence is geographically clustered in rural regions, mapping the location of disease-occurrence can be used to identify high-risk areas for prevention activities. Geographic information systems (GIS) have emerged as a new way to collect and manage outbreak data related to location and time
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