Risk Factor and Cluster Analysis to Identify Malaria Hot Spot for Control Strategy in Samigaluh Sub-District, Kulon Progo, Indonesia

Background: In 2015, Indonesia government targeted to eliminate malaria in Java Island. Nevertheless, until now malaria still occurs, including in Samigaluh, Kulon Progo District although many malaria programs has been run. Complexity and dynamic of the population also limited budget may become the reason of malaria combat difficulties. Subsequently, a method to direct the policymaker on how to provide program effectively and efficiently was needed. We examined malaria risk factor using statistical and cluster analysis. Methods: A quantitative study with case-control approach was conducted during Spring 2017 in Samigaluh II Public Health Centre, Indonesia. The structured questioner was used to collect the information from both of case and control which were people who had blood examination regarding malaria diagnosed during January-December 2016. Global Positioning System was used to record the geographical position of house participant which was used in cluster analysis. Results: Occupation was recognized as the significant risk factor to malaria. One most likely cluster was detected and translated as the source of transmission because of its fall in malaria hotspot. Conclusion: Satscan be able to detect a spatial cluster of malaria case and a promising method for supporting malaria control.