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Title: Seasonal geographical access to healthcare in Cross River State, Nigeria
Author: Otu, Edet
ISNI:       0000 0004 7972 0229
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2019
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Background: Geographical access to healthcare is a significant public health issue in developing countries. The problem becomes more complicated in the wet season when road transport is usually interrupted due to flooding. However, healthcare care accessibility studies have largely ignored the seasonality of geographical access let alone associating it with disease outcomes or accommodating it in the plan to increase access to health services. Therefore, this study carried out a community-level investigation of seasonal geographical access to health facilities, its influence on malaria outcomes and on the potential locations of new health facilities. Method: A systematic review of geographical access to healthcare in Low-and-Middle-Income-Countries (LMICs) was conducted. Health facilities and road network data were obtained from the Local Authority. Facilities' locations were digitised from high-resolution Orthophoto Map and Google Map. Data on the geographical distribution of the population were projected from the community-level census record. A flood model was used to measure access in the wet season by driving and walking times. Trips to health facilities and potential locations of new facilities were assessed using the ArcGIS Network Analyst Tool. Logistic regression in SPSS was used to examine associations between drive times to health facilities and malaria outcomes. Results: Average drive times to health facilities were longer in the wet season compared to the dry season. While the whole population could access health facilities in the dry season, 70%, 37% and 68% of the population could access PHC, hospitals and NHIS in the wet season respectively. There was no compelling evidence that the odds of malaria increased in the wet season, although there were a few associations. The dry season Location-Allocation Models (LAMs) produced better population coverage than the wet season. Conclusion: Measurement of geographical access without including the wet season can produce misleading results. Therefore, seasonal variability of geographical access should become an essential part of accessibility studies and healthcare planning.
Supervisor: Maheswaran, Ravindra ; Jordan, Hannah Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available