Spatial-Temporal Analysis for Identification of Vulnerability to Dengue in Seremban District, Malaysia

Abstract

Dengue is a major public health threat in Malaysia, which is known for the hyperendemicity with all the four serotypes of the dengue virus circulating concurrently. Annual dengue cases reported were 43,000 cases for 2013, and this imposed a heavy toll on the resources for dengue prevention and control program. The objective of mapping in our study is to determine the spatial clustering of the dengue cases and to identify the areas that are vulnerable to dengue outbreaks. A Geographical Information System (GIS) was used to assess the vulnerability of Seremban district. Dengue data were obtained from the Ministry of Health. We determined the spatial distribution, the average distance of dengue cases and identified hotspots areas using the Moran’s I, Average Nearest Neighbourhood (ANN), Kernel density estimation. Vulnerability to dengue was assessed with the spatial temporal analyses and Local Indicator for Spatial Autocorrelation (LISA). From 2003-2009 Seremban recorded 6076 dengue cases. Moran’s I showed the cases occurred in clusters with a Z-score of 16.384 (p lesss than 0.001). ANN 0.264 (p less than 0.001) indicated the mean distance between every dengue case was 55 meters. Kernel density estimation showed hotspots of dengue were concentrated in two subdistricts. This paper discusses how spatial-temporal approach can be used to assess the vulnerability of Seremban to dengue where control activities can be more focused to these high risk areas. Mapping the dengue distribution using spatial-temporal approach is useful and guides the public health management of dengue.