Spatio-Temporal analysis of Dengue distribution pattern in Kuantan from 2015-2019

Abstract

Dengue fever is a health issue that has been a source of concern throughout Malaysia, notably Kuantan, Pahang. Dengue fever cases have been recorded on a regular basis in the local community in recent years. This study aimed to examine the spatio-temporal pattern based on yearly dengue surveillance data for five years from 2015 to 2019. To better understand the pattern of dengue cases, a descriptive analysis that included extensive observation of dengue data as well as the distribution of rainfall in Kuantan was carried out in this study. Data on dengue case distributions over a five-year period were gathered from the “eDengue” system. A total of 6560 dengue cases in Kuantan was used in this study. Spatio-temporal analysis was performed by plotting the dengue cases distribution using the Geographic Information Systems (GIS) software and applied with the Kernel Density analysis to trace locality patterns in dengue hotspot. The GIS analysis shows centralized hotspot pattern of dengue cases which mostly focus on the sub-district of Kuala Kuantan. Then, the dengue cases distribution pattern was analysed against the rainfall distribution. The statistical analysis by using the Pearson correlation were used to find the relationship between dengue cases and rainfall. The Pearson correlation brought the value of the R2 linear (R2 = 0.003) which is far from the accepted value by the research community (R2 = 0.19). The Pearson correlation value (r = 0.053) was not close enough to the significance value (r = 1). Moreover, the significance 2-tailed value is more than 0.5 which means means that the relationship between dengue and rainfall in Kuantan from 2015 till 2019 was not statistically significant. These findings show a clear spatio-temporal trend of dengue cases in Kuantan and no significance between dengue cases and rainfall pattern, providing evidence in directing future works on researching of the dengue distribution cases and providing the effective solution in the area with high dengue cases.