Abstract
BackgroundIn low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets.MethodsA total of 1601 patient data that were retrieved from unit tuberculosis registers were included in the final analyses. The population and geo-location data were obtained from the Central Statistical Agency of Ethiopia. Altitude data were extracted from ASTER Global Digital Elevation Model Version 2. Aggregated datasets from sample of 169(40%), 254(60%) and 338(80%) kebeles were used to estimate the spatial risk of TB distribution in the Gurage Zone by using a geostatistical kriging approach. The best set of input parameters were decided based on the lowest prediction error criteria of the cross-validation technique. ArcGIS 10.2 was used for the spatial data analyses.ResultsThe best semivariogram models were the Pentaspherical, Rational Quadratic, and K-Bessel for the 40, 60 and 80% spatial datasets, respectively. The predictive accuracies of the models have improved with the true anisotropy, altitude and latitude covariates, the change in detrending pattern from local to global, and the increase in size of spatial dataset. The risk of tuberculosis was estimated to be higher at western, northwest, southwest and southeast parts of the study area, and crossed between high and low at west-central parts.ConclusionThis study has underlined that the geostatistical kriging approach can be applied to estimate the spatial risk of tuberculosis distribution in data limited settings. The estimation results may help local public health authorities measure burden of the disease at all locations, identify geographical areas that require more attention, and evaluate the impacts of intervention programs.
Highlights
In low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units
Study area This study was conducted in the Gurage Zone in southern Ethiopia, which is located between 7°76′ and 8°45’ N
The health centers carry out all activities as health posts and clinics, and provide intensified case finding, sputum microscopy services, provide isoniazid preventive therapy for eligible persons, diagnose and manage adverse drug reactions and other complications, carry out Human Immunodeficiency Virus-associated TB (TB/Human Immunodeficiency Virus (HIV)) collaborative activities, refer smear negative presumptive TB, extra-pulmonary TB and Drug Resistant TB (DR-TB) patients to higher level facilities, provide support to health post staff, keep patient records and manage medicines stocks, plan and implement TB infection control
Summary
In low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets. The global distribution of the disease is skewed heavily toward low-and-middle income countries, which accounted for about 87% of all estimated incident cases. It is difficult to obtain spatially complete data on TB in Ethiopia [1, 2]. Other regional reports did not show continuous spatial distribution and burden of the disease within-and-between smaller geographical
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