Spatial Analysis of Public Health Data in Ghana: a case study of exploratory spatial analysis of Diarrhoea

Abstract

Background: Diarrhoea is a  public health burden amongst the top five causes of premature death  and disability-adjusted life years in the tropical regions. In Ghana, diarrhoea has been identified as the second most common health problems treated in outpatient visits. Evaluations of diarrhea prevention efforts suggested that the best prevention strategies of diarrhoea may vary by location. For this reason, spatial statistical tools such as Geographical Information System (GIS)  has been applied expansively in health research to improve public health since 1980s. There are, however, extremely few of such studies in Ghana and there had not been any known nationwide study of the spatial distribution of diarrhoea in Ghana. In this study, we aimed to use exploratory spatial analysis techniques of GIS to assess the spatial epidemiological distribution of diarrhoea in Ghana and to locate the hotspot areas that need further focused public health interventions.

Method: The outpatient department morbidity data of diarrhoea cases over the periods of 2010 to 2014 was obtained from Ghana Health Service and geo-coded using ArcGIS 10.1 according to the 170 administrative districts of Ghana. Incidence rates were estimated  and spatially smoothen with Empirical Bayesian Smoothing (EBS) technique to avoid unbiased visual interpretation. The EBS rates were mapped and classified using defined interval classification system. Global Moran's I and the Anselin Local Moran's I were computed with ArcGIS to respectively test for the evidence of space-time variation in the incidence of diarrhoea and to identify areas of relatively high and/or low rates.

Results: This study described the spatial distribution of  diarrhoeal infection by assessing the global and local occurrence of the incidence rates of diarrhoea at district levels in Ghana. Mapping the smoothed incidence rates of diarrhoea geo-visually pointed spatial patterns and with generally increasing rates over the years 2010 to 2014. Evaluating the observed non-random spatial patterns, the global Moran's I confirmed significant geographical epidemiological patterns with significant spatial clustering (Moran's I > 0, Z > 1.96, p < 0.05). These spatial patterns were decreasing spatio-temporally from 2010 to 2013 but suddenly increased to the highest clustering in 2014. Cluster-outlier analysis with local Moran's I_i spatio-temporally identified a number of areas with statistically significant measures of relatively high and/or low clustering of rates.

Conclusion: The results of the exploratory spatial analysis disclosed the grave necessity of spatial analysis to improve  public health, surveillance and disease prevention strategies in Ghana. The rate of diarrhoea still remains very high in Ghana with significant geographical and temporal variations. This suggests possible inequalities in healthcare services and health intervention programmes and relatively more risk factors in some areas. This study also suggests that diarrhea prevention strategies should be location-specific, while considering the neighbouring locations. The few identified hotspot districts with the most likely endemic clusters of diarrhoea cases need extra health intervention programmes and prioritisation.

Keywords: Spatial epidemiology, diarrhoea, hotspot, spatial analysis, Geographical Information System (GIS), Moran's I, Ghana