Olalekan A Uthman1. 1. Center for Evidence-based Global Health, Ilorin, Kwara State, Nigeria. uthlekan@yahoo.com
Abstract
OBJECTIVE: To investigate the geographical and temporal distribution of tuberculosis in Africa in order to identify possible high-risk areas. DESIGN: Time-trend and spatial analyses. DATA SOURCES: World Health Organization Statistical Information System and U.S. Census Bureau International Data Base. METHODS: Time trends in the 15-year study period from 1991 to 2005 were analyzed by Poisson regression models. Global Moran's I and Moran Local Indicators of Spatial Associations were used to test for evidence of global and local spatial clustering, respectively. RESULTS: Southern, Eastern and Middle Africa experienced an upward trend in the number of reported cases of tuberculosis (TB). The number of Northern African TB cases declined steadily over the 15-year study period. The spatial distribution of TB cases was nonrandom and clustered, with a Moran's I = 0.492 (p = .001). Spatial clustering suggested that 25 countries were at increased risk of tuberculosis, and ten countries could be grouped as "hot spots." CONCLUSIONS: The study identified spatial and temporal patterns in tuberculosis distribution, providing a means to quantify explicit tuberculosis risks and laying a foundation to pursue further investigation into the environmental factors responsible for increased disease risk. This information is important in guiding decisions on tuberculosis control strategies.
OBJECTIVE: To investigate the geographical and temporal distribution of tuberculosis in Africa in order to identify possible high-risk areas. DESIGN: Time-trend and spatial analyses. DATA SOURCES: World Health Organization Statistical Information System and U.S. Census Bureau International Data Base. METHODS: Time trends in the 15-year study period from 1991 to 2005 were analyzed by Poisson regression models. Global Moran's I and Moran Local Indicators of Spatial Associations were used to test for evidence of global and local spatial clustering, respectively. RESULTS: Southern, Eastern and Middle Africa experienced an upward trend in the number of reported cases of tuberculosis (TB). The number of Northern African TB cases declined steadily over the 15-year study period. The spatial distribution of TB cases was nonrandom and clustered, with a Moran's I = 0.492 (p = .001). Spatial clustering suggested that 25 countries were at increased risk of tuberculosis, and ten countries could be grouped as "hot spots." CONCLUSIONS: The study identified spatial and temporal patterns in tuberculosis distribution, providing a means to quantify explicit tuberculosis risks and laying a foundation to pursue further investigation into the environmental factors responsible for increased disease risk. This information is important in guiding decisions on tuberculosis control strategies.
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