Mapping Of Epidemiological Variabeles For Diarrhea Cases In The Oesapa Community Health Center Working Area In 2024

Jelin Lawalu; Maria M. D. Wahyuni

doi:10.51556/ejpazih.v15i1.536

Authors

Jelin Lawalu Public Health Study Program, Faculty of Public Health, Nusa Cendana University
Maria M. D. Wahyuni Public Health Study Program, Faculty of Public Health, Nusa Cendana University

DOI:

https://doi.org/10.51556/ejpazih.v15i1.536

Keywords:

Diarrhea, Spatial analysis, GIS, Epidemiology, Health center Oesapa

Abstract

Background: Diarrhea remains a major public health concern in developing countries like Indonesia, particularly among children under five. Objectives: Spatial analysis using Geographic Information Systems (GIS) can help visualize disease patterns, identify risk factors, and guide interventions. Method: This descriptive quantitative study employed a spatial mapping approach. A total of 416 diarrhea cases reported in 2024 at Health center Oesapa, Kota Kupang, were included using total sampling. Secondary data were obtained from health records. The dependent variable was diarrhea incidence; independent variables included age, gender, nutritional status, time, and location. Results: The results This study was conducted in the working area of Health center Oesapa, which includes five urban villages: Oesapa, Lasiana, Kelapa Lima, Oesapa Barat, and Oesapa Selatan. Based on data from 2024, a total of 416 diarrhea cases were recorded, with uneven distribution across these areas. The highest number of cases was found in Urban village Oesapa, with 160 cases (38.5%), followed by Lasiana with 148 cases (35.6%). Meanwhile, Oesapa Barat recorded 67 cases, Kelapa Lima 32 cases, and Oesapa Selatan had the fewest, with 9 cases. These findings indicate that Oesapa and Lasiana are high-priority areas for diarrhea prevention and control, as they fall into the high distribution category. Conclusion: Spatial mapping revealed that age, gender, nutrition, and environmental factors significantly affect diarrhea distribution. GIS provides an effective tool to identify high-risk areas and support targeted public health interventions.

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