Space-Time Analysis for Dengue Surveillance: A Case Study in Sleman, Yogyakarta, Indonesia

Introduction: Surveillance is a dynamic activity that needs a continuous update to perform their function such as monitoring, evaluating, identifying high risk and supporting disease policy making. Geographic Information System (GIS) is a system for capture, store, analysis and visualise a phenomenon related to the geographical position including related particular disease. This tool is claimed powerful to support disease surveillance. Objective: This study aims to apply retrospective space-time analysis using GIS on dengue cases to identify the clustering that may occur during the data period for supporting dengue surveillance. Method: This research was a descriptive study by employed GIS technique-Satscan retrospective spacetime permutation model. 159 confirmed dengue case sourced from Sleman District Health Office (Sleman DHO) between January 2017 to September 2018 was used as an input data. Geographical Positioning System (GPS) was employed to collect the coordinate location of the cases. The map was generated using Arc GIS. Results: A most likely cluster and eight secondary clusters were detected in this study. The most likely cluster was found in Depok subdistrict during the middle of March to the middle of April 2018. Conclusions: GIS shown as a powerful tool for dengue surveillance. Identification of space and time related to dengue is an alarm for related stakeholder on dengue prevention to prepare and prevent outbreak occurrence.