SPATIAL DISTRIBUTION OF DIARRHEAL CASES: THE INTERPLAY BETWEEN POPULATION DENSITY, SANITATION, AND HEALTH FACILITY ACCESSIBILITY IN NORTH SUMATERA PROVINCE 2022-2023

Authors

  • Desy Widyastuti Sumatera Utara
  • Mulyana Universitas Sari Mutiara Indonesia
  • Vita Diah Rivani Universitas Sari Mutiara Indonesia
  • Stefya Natasya Sari Sinaga Universitas Sari Mutiara Indonesia
  • Elyzabeth Arihta Sinulingga Universitas Sari Mutiara Indonesia
  • Vierto Irennius Girsang Universitas Sari Mutiara Indonesia

DOI:

https://doi.org/10.60050/pwh.v6i2.99

Keywords:

Diarrhea, Spatial Analysis, QGIS

Abstract

Background: Diarrhea remains a major public health problem in Indonesia, especially in areas with high population density and poor access to sanitation. North Sumatra Province experiences fluctuations in diarrhea cases, with the number of cases reaching 205,155 in 2022 and decreasing to 95,433 in 2023.

Objectives: This study aims to map the spatial distribution of diarrhea cases in North Sumatra Province in 2022-2023, and analyze its relationship with population density, access to proper sanitation, and the number of health facilities.

Methods: This study used a quantitative descriptive approach using secondary data obtained from the Central Statistics Agency (BPS) of North Sumatra Province. The area covered 33 regencies/cities. The variables analyzed included the number of diarrhea cases, population density, access to proper sanitation, and the number of health facilities. Spatial analysis was conducted using QGIS version 3.28 (Firenze) using the Join Attribute Table technique and thematic map visualization using the Graduated Symbology method.

Results: There was a shift in the spatial pattern of diarrhea cases from 2022 to 2023, with the highest number of cases shifting from Medan City (40,126 cases) to Deli Serdang Regency (16,108 cases). Areas with poor sanitation and high density tend to have higher diarrhea rates. Meanwhile, the number of health facilities does not always correlate with a decrease in diarrhea cases.

Conclusion: A spatial approach can reveal disease distribution patterns based on regions more comprehensively. Regular use of Geographic Information Systems is recommended to support infectious disease monitoring and spatial data-based policymaking, including the development of predictive dashboards for early warning and resource allocation.

References

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Published

2025-07-29

How to Cite

Widyastuti, D., Mulyana, Rivani, V. D., Sinaga, S. N. S., Sinulingga, E. A., & Girsang, V. I. (2025). SPATIAL DISTRIBUTION OF DIARRHEAL CASES: THE INTERPLAY BETWEEN POPULATION DENSITY, SANITATION, AND HEALTH FACILITY ACCESSIBILITY IN NORTH SUMATERA PROVINCE 2022-2023. PRIMA WIYATA HEALTH, 6(2), 130–140. https://doi.org/10.60050/pwh.v6i2.99