The Implementation of Spatial Weighted Regression on Detecting the Risk Factors of Malaria Incidences In Kulonprogo District

Abstract

Malaria is still a public health problem caused by Plasmodium parasites. This disease is naturally transmitted through the bite of female Anopheles mosquitoes. Kulonprogo Regency is one of the malaria endemic areas that needs to be developed to combat malaria. This research aims to describe the distribution of malaria cases to determine vulnerable areas in Kulonprogo Regency. This research was an observational analytic with cross sectional design conducted in April - October 2018. This research used the total sampling of 62 malaria cases. Data analysis was performed by using a Geographic Information System approach with overlay, buffer, cluster techniques, and spatial weighted regression. Based on the results of the partial analysis, it was found that 62 cases of malaria spread in 6 sub-districts namely: Kokap, Pengasih, Samigaluh, Kalibawang, Wates and Sentolo. The distribution of malaria cases clustered in Kokap Sub District, namely in Kalirejo Village (29 cases) and Hargorejo Village (9 cases). The overlay and buffer techniques found that the distribution of cases spread in Menoreh hills which have forest vegetation. Malaria-prone areas in Kulonprogo Regency were found in Kalirejo Village and Hargorejo Village through the results of spatial analysis using a Geographic Information System approach. Thus, malaria control efforts were focused on these vulnerable areas.