SPATIAL INTELLIGENCE IN URBAN HEALTH: A GIS-BASED ANALYSIS OF HEALTHCARE FACILITY DISTRIBUTION IN UYO, NIGERIA

Authors

  • Elijah, D. U Department of Geography and Natural Resources Management, University of Uyo, Uyo Author
  • Inwang, S.E Department of Geography and Natural Resources Management, University of Uyo, Uyo Author
  • Jimmy, U.J. Department of Geography and Natural Resources Management, University of Uyo, Uyo Author
  • James, U Department of Geography and Natural Resources Management, University of Uyo, Uyo Author
  • Richard, T Department of Geography and Natural Resources Management, University of Uyo, Uyo Author
  • Udofia, U Department of Geography and Natural Resources Management, University of Uyo, Uyo Author

Keywords:

Geographic Information Systems (GIS) based techniques, Health Care Facilities (HCF), Spatial Distribution, Nearest Neighbour Analysis, Uyo Capital City, Nigeria

Abstract

This study employed Geographic Information Systems (GIS) techniques to map and evaluate the inventory and spatial distribution of Healthcare Facilities (HCF) in Uyo Capital City, Nigeria. Utilizing handheld Global Positioning System (GPS) devices for field data collection and ArcGIS 10.8 for spatial analysis, the research identified a total of 64 healthcare facilities within the study area. An inventory analysis revealed a significant structural imbalance: 14 facilities (22.6%) are categorized as Primary Health Care (PHC), 49 (76.6%) as Secondary facilities—predominantly privately owned—and only one (1.6%) as a Tertiary facility. The spatial pattern of distribution was assessed using Nearest Neighbour Analysis, yielding a Nearest Neighbour Ratio of 0.603357 and a highly significant z-score of -5.926470 (p < 0.01). These statistics confirm a significantly clustered distribution pattern, concentrated primarily within the city center (Eniong, Oku, Uyo, and Aka regions) while leaving the suburban fringes underserved. Furthermore, the study evaluated accessibility based on the World Health Organization (WHO) standard walking distance of 4km. The findings indicate that while central urban residents enjoy high proximity, peripheral communities such as Ikot Udo Ibiono and Mbiakong Uruan suffer from locational disadvantage and increased travel burdens. This "Inverse Care Law" manifestation suggests that private-sector dominance has driven facilities toward high-population density areas at the expense of equitable spatial coverage. The study concludes that the current distribution is uneven and inadequate for the city’s projected growth. It recommends the strategic siting of new public PHCs in identified "blind spots" and the use of GIS-driven suitability modeling by the Ministry of Health to ensure that healthcare delivery transitions from a clustered luxury to a spatially accessible right for all citizens.

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Published

2025-12-31

How to Cite

D. U, E. ., S.E, I. ., U.J., J. ., U, J. ., T, R., & U, U. . (2025). SPATIAL INTELLIGENCE IN URBAN HEALTH: A GIS-BASED ANALYSIS OF HEALTHCARE FACILITY DISTRIBUTION IN UYO, NIGERIA. Civil Engineering & Urban Development Review , 1(1), 22-31. https://technology.tresearch.ee/index.php/CEUDR/article/view/68