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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3408

Title: STATISTICAL ANALYSIS OF SPATIAL DISTRIBUTION OF TUBERCULOSIS IN NORTH SHOA ZONE, ETHIOPIA
Authors: Habte, Tadesse
Advisors: Butte Gotu(Dr.)
Keywords: Spatial Distribution
Tuberculosis
Shoa
Copyright: May-2011
Date Added: 18-Jul-2012
Publisher: Addis Ababa University
Abstract: Tuberculosis (TB) is the major cause of health problems in Ethiopia, accounting for more than thousands of cases and deaths occurring annually. The risks of morbidity and mortality associated with TB are characterized by spatial variations across the country. For instance, Oromia is a region with the largest number of TB cases in Ethiopia (36.80%) and the share of North Shoa Zone is really quite big (FMOH, 2008). This study examines the spatial patterns of TB in North Shoa Zone and identifies those variables that determine TB clustering. We examine the global and local patterns of TB distribution by using individual morbidity data collected from North Shoa Health Bureau in 2008. Global Moran’s I, Geary’s C and Moran scatter plot are used in determining distribution of TB. These were used in identifying areas of hot spot for giving strong care in monitoring and to reduce TB distribution. The values for Global Moran’s I shows that the presence of significant TB clustering in North Shoa Zone. And in six woredas significant TB clustering of similar values were observed by using cluster map while only in one woreda a significant TB clustering of dissimilar values was observed. Furthermore, Poisson and negative binomial regression analysis are used in this study. The findings of these models have shown that all explanatory variables (population density, number of health centers and prevalence of HIV cases) are significantly associated with TB case loading. There is evidence of significant TB clustering in North Shoa Zone. Significant hot spots and cold spots of TB clusters were identified in six woredas. Poisson and negative binomial regression analysis show a decrease in TB case loading with increasing number of health centers. Additionally, it is population density that is highly associated with TB case loading.
Description: A THESIS SUBMITTED TO THE SCHOOL OF GRADUATE STUDIES OF ADDIS ABABA UNIVERSITY IN PARTIAL FULLFILLEMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN STATISTICS
URI: http://hdl.handle.net/123456789/3408
Appears in:Thesis - Statistics

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