International journal of health geographics · 2006
Investigation of geo-spatial hotspots for the occurrence of tuberculosis in Almora district, India, using GIS and spatial scan statistic.
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Tiwari Neeraj, Adhikari C M S, Tewari Ajoy, Kandpal Vineeta
Аннотация
BACKGROUND: The World Health Organization has declared tuberculosis a global emergency in 1993. It has been estimated that one third of the world population is infected with Mycobacterium tuberculosis, the causative agent of tuberculosis. The emergence of TB/HIV co-infection poses an additional challenge for the control of tuberculosis throughout the world. The World Health Organization is supporting many developing countries to eradicate tuberculosis. It is an agony that one fifth of the tuberculosis patients worldwide are in India. The eradication of tuberculosis is the greatest public health challenge for this developing country. The aim of the present population based study on Mycobacterium tuberculosis is to test a large set of tuberculosis cases for the presence of statistically significant geographical clusters. A spatial scan statistic is used to identify purely spatial and space-time clusters of tuberculosis.
RESULTS: Significant (p < 0.05 for primary clusters and p < 0.1 for secondary clusters) high rate spatial and space-time clusters were identified in three areas of the district.
CONCLUSION: There is sufficient evidence about the existence of statistically significant tuberculosis clusters in Almora district of Uttaranchal, India. The spatial scan statistics methodology used in this study has a potential use in surveillance of tuberculosis for detecting the true clusters of the disease.
RESULTS: Significant (p < 0.05 for primary clusters and p < 0.1 for secondary clusters) high rate spatial and space-time clusters were identified in three areas of the district.
CONCLUSION: There is sufficient evidence about the existence of statistically significant tuberculosis clusters in Almora district of Uttaranchal, India. The spatial scan statistics methodology used in this study has a potential use in surveillance of tuberculosis for detecting the true clusters of the disease.