Determinants and Spatial Distribution of HIV/AIDS in Jimma Zone, Southwest Ethiopia

Abstract

Background: HIV is a major cause of illness and death in large parts of the developing countries, especially in Africa. Accurate estimates of HIV distribution are required for planning, implementation and evaluation of HIV control programs. Studies that shows the comparison of distribution of HIV over place to place in Ethiopia specially at Jimma Zone with at Woreda level is very limited. Hence, this study did investigate the spatial distribution of HIV and associated factors at Wereda level in Jimma Zone. Objectives: The main objective of this study was to examine spatial patterns and risk factors of HIV distribution in Jimma zone, Oromia Region, Ethiopia. Methodology: The study was conducted in Jimma zone of entire districts and the data is secondary which is obtained from Jimma zone health center. Spatial distribution of HIV were identified using global and local measures of spatial auto correlation. Binary regression model was used to analyze covariates related to HIV distribution using R software and to analyze spatial point pattern data relevant software GeoDa and ArcGIS were used. Results: The results of this study indicated that, the presence of significant global spatial autocorrelation of HIV Distribution in Jimma zone. Based on the p-values of Moran’s I(0.002 < 0.05) and Geary’s C(0.0009 < 0.05) coefficients, we reject the null hypothesis of no spatial autocorrelation. The results of binary regression model including spatial dependence show that, there is statistically significant relationship between HIV status and Age, Marital status,religion,and place of residence. Conclusions: There is evidence of significant HIV clustering in Jimma zone, southwest Ethiopia. Significant hot spots clusters were identified in eight districts and cold spots of HIV clusters were identified in ten districts. Clustering of dissimilar values identified in four Woreda. Model based data analysis showed that there is significant relationship between HIV distribution and Age,Gender,Marital status,Education level,religion,residence and condom use. The study recommends that interventions should be facilitated in highly clustered HIV distribution areas by giving special attention in targeting intervention and health services to the highly risk exposed districts and neighboring districts.