Towards Sustainable Distribution of Health Centers Using GIS: A Case Study from Nigeria
Published: 2011-10-05
Page: 130-136
Issue: 2011 - Volume 1 [Issue 3]
Michael Oloyede Alabi *
Department of Geography and Planning, PMB 1008, Kogi State University, Anyigba, Kogi State, Nigeria
*Author to whom correspondence should be addressed.
Abstract
Aim: This research is aimed to assess the spatial distribution of health centres in Lokoja, Nigeria.
Study design: Case study.
Place and Duration of Study: Lokoja is located in Kogi State of Nigeria and lies within latitude 7º45’N and 7º51N and longitude 6º41’E and 6º45’E of Greenwich meridian, between June 2010 and may 2011.
Methodology: This study was conducted within 5 neighborhoods in the study area. The Global Positioning System (GPS) was used to pinpoint the location of existing health centres. The inferential statistical tool applied in analyzing the data in this research is the “Nearest Neighbour Analysis” (NNA); this was used in establishing the distribution pattern of public and private health centres in the study area. Nearest Neighbour Analysis is the method of exploring pattern in the locational data by comparing mean distance (Do) of the phenomena in question to the same expected mean distance (De) usually under a random distribution.
Results: An output of 0.99228 was found, an indication of weak randomness, because it exceeds the Z-score table value of -0.723417 which is indicative of insignificant accessibility. This scenario is a microcosm of state of health facility distribution in typical Nigerian cities where health facility distributions do not adhere to any particular pattern or criteria
Conclusion: In the area where population is not evenly distributed, the mean centre of population distribution is calculated as the “demand”, which forms the origin of location. The facility location point is considered as destination points or “supply”. The travel time can then be estimated as the shortest time through the road networks between the pair of population and the healthcare facility locations. The best route can then be created using network data set and network analysis in arc/info.
Keywords: Health care delivery, health infrastructure, equitable distribution, GIS