MAPPING PNEUMONIA IN TODDLERS: THE ROLE OF POPULATION DENSITY, SANITATION, AND HEALTH FACILITIES IN NORTH SUMATERA PROVINCE 2022-2023
DOI:
https://doi.org/10.60050/pwh.v7i1.100Keywords:
Pneumonia In Children, Spatial Analysis, QGISAbstract
Background: Pneumonia is a serious public health problem in Indonesia, particularly among toddlers. Toddlers are the most vulnerable group due to their immature immune systems. Environmental factors such as population density, poor sanitation, and limited healthcare facilities contribute to the high incidence of pneumonia. In Indonesia, pneumonia remains one of the diseases with the highest healthcare costs.
Objectives: This study aims to map the spatial distribution of pneumonia cases among toddlers in North Sumatra Province in 2022–2023 and analyze its relationship to environmental factors such as population density, access to proper sanitation, and the number of healthcare facilities.
Methods: This is a quantitative study with an area-based ecological design and a spatial analysis approach. Secondary data from the North Sumatra Statistics Agency (BPS) was analyzed using QGIS software with a spatial overlay method to evaluate spatial relationships between variables.
Results: The study shows that in 2022, the highest number of pneumonia cases occurred in Deli Serdang Regency (1,322 cases), and in 2023, this number increased to 2,453 cases. Medan City, with the highest population density, also recorded high numbers of cases (81 cases in 2022 and 1,001 cases in 2023). South Nias Regency, with the lowest sanitation access (12.23% in 2022), recorded low numbers of cases (0–6 cases). Areas with high levels of health facilities, such as Medan and Deli Serdang, continued to record high numbers of cases, while areas like Pakpak Bharat, with low facilities, recorded no cases.
Conclusion: The distribution of pneumonia cases in children under five in North Sumatra is influenced by a combination of environmental factors. The highest number of cases occurs in areas with high density and abundant health facilities, but this is not always commensurate with access to sanitation. Spatial analysis helps identify risk areas and informs public health intervention planning.
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