GIS-Based Spatial Mapping of Dengue Hemorrhagic Fever Cases in Seyegan, Ngaglik 1, and Minggir Primary Healthcare Areas, Sleman Regency

Abstract

Introduction: Dengue hemorrhagic fever (DHF) remains a public health problem in Sleman Regency and requires location-based information to guide control priorities. This study aimed to map case distribution and analyze the spatial pattern of DHF exclusively within three selected primary health-care catchment areas representing the highest case counts in Sleman Regency.

Methods: A retrospective quantitative descriptive spatial study analyzed all 108 confirmed cases in these three selected areas (Seyegan, Ngaglik 1, and Minggir) using frequency distributions, incidence rates, point mapping, and Average Nearest Neighbor (ANN) in Microsoft Excel and ArcGIS 10.3.

Results: Of 423 cases across 25 primary health-care centers, Seyegan recorded 42 cases (IR 78.94/100,000 population), Ngaglik 1 recorded 33 cases (IR 60.59/100,000), and Minggir recorded 33 cases (IR 100.51/100,000); all three were classified as high-incidence areas. Based on ANN analysis, there was insufficient evidence to reject the assumption of spatial randomness in Seyegan (NNR 0.894913; p=0.192616), Ngaglik 1 (NNR 1.034989; p=0.700593), and Minggir (NNR 1.029359; p=0.746962). Regarding the distribution of reported cases, individuals aged 15–44 years (58.3%) and males (57.4%) accounted for the highest proportions; however, this does not necessarily indicate a higher risk as population denominators for these specific groups were not assessed. Meanwhile, the monthly rainfall–case pattern was nonlinear.

Conclusion: The different rankings produced by case counts and incidence rates emphasize the importance of population denominators when comparing disease burdens. GIS serves as a valuable tool for visualizing disease distribution in high-incidence areas; however, to directly determine intervention priorities and vector control, this spatial mapping must be further integrated with comprehensive entomological and environmental data.

Keywords: ArcGIS; Average Nearest Neighbor; Dengue hemorrhagic fever; Geographic information system; Spatial mapping