1. Modelling geographic accessibility to Primary Health Care Facilities: combining open data and geospatial analysis.
- Author
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Lawal, Olanrewaju and Anyiam, Felix E.
- Subjects
HEALTH facilities ,PRIMARY care ,GEOSPATIAL data ,HEALTH services accessibility ,HEALTH planning ,CITY dwellers ,LONG-term care facilities - Abstract
Ensuring healthy lives and promoting well-being for all ages is the 3rd Sustainable Development Goal (SDG). Inequality in access to health care remains one of the primary challenges in achieving the goal. With the ever-increasing expansion of urban areas and population growth, there is a need to regularly examine the pattern of accessibility of basic amenities across regions, States and urban areas. This study examined geographic access to Primary Health Care Facilities (PHCF) in Nigeria using the combination of open data and geospatial analysis techniques. Thus, showcasing an approach can be replicated across different regions in Sub-Saharan Africa due to issues of information gap. Data on elevation, location of health care facilities, population and network data were utilised. The result shows that PHCF aggregate at certain locations, e.g. major urban agglomerations, and transit route leading to these places. High concentrations are found in the capital city. The average travel time to the nearest PHCF is about 14 min (Standard Deviation ±13.30 min) while the maximum is about 2 hours. Pockets of low accessibility areas exist across the Akwa Ibom State in the Niger Delta region of Nigeria. There is an indication that most places have good geographic access. Across the 1787 settlements identified in our dataset, 98.3% are with good access (<30 min), 27 settlements are located in the poor access class (31–60 min), while two settlements are within the very poor access class (>60 min). Geographic access is not the main limiting factor to health care access in the region. Therefore, computation of access to health care should take into consideration other dimensions of accessibility, to create a robust measure which will support effective and efficient health care planning and delivery. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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