GEOSPATIAL OPTIMIZATION OF EMERGENCY RESPONSE ROUTES USING GIS AND DIJKSTRA’S ALGORITHM: A CASE STUDY OF UNIVERSITY OF BENIN TEACHING HOSPITAL, NIGERIA
Abstract
Emergency response times are critical in determining patient outcomes in urban healthcare settings. The University of Benin Teaching Hospital (UBTH) serves a densely populated region of Benin City, Nigeria, where efficient route planning is essential for rapid medical intervention. This study employs Geospatial Information System (GIS) tools and Dijkstra’s algorithm to analyze and optimize emergency routes within a 6.5 km catchment area of UBTH. Road network data, population density, and service areas were integrated into a spatial database and analyzed using ArcGIS 10.8. The shortest travel paths and times from various strategic locations, including New Benin Market, Egor Market, Evbuotubu, Ziko Gas, and National Museum, were computed. Results show that New Benin Market provides the shortest access to UBTH at 5.2 km in approximately 8 minutes, while Ziko Gas yielded the longest route at 8.5 km in 13 minutes. These findings show the critical role of geospatial technologies in improving emergency healthcare delivery and minimizing patient morbidity and mortality rates through timely interventions.
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