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      Investigation of geo-spatial hotspots for the occurrence of tuberculosis in Almora district, India, using GIS and spatial scan statistic

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          Abstract

          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.

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          Most cited references33

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          Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico.

          This article presents a space-time scan statistic, useful for evaluating space-time cluster alarms, and illustrates the method on a recent brain cancer cluster alarms in Los Alamos, NM. The space-time scan statistic accounts for the preselection bias and multiple testing inherent in a cluster alarm. Confounders and time trends can be adjusted for. The observed excess of brain cancer in Los Alamos was not statistically significant. The space-time scan statistic is useful as a screening tool for evaluating which cluster alarms merit further investigation and which clusters are probably chance occurrences.
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            Prospective time periodic geographical disease surveillance using a scan statistic

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              Exploratory space-time analysis of reported dengue cases during an outbreak in Florida, Puerto Rico, 1991-1992.

              The spatial and temporal distributions of dengue cases reported during a 1991-1992 outbreak in Florida, Puerto Rico (population = 8,689), were studied by using a Geographic Information System. A total of 377 dengue cases were identified from a laboratory-based dengue surveillance system and georeferenced by their residential addresses on digital zoning and U.S. Geological Survey topographic maps. Weekly case maps were generated for the period between June and December 1991, when 94.2% of the dengue cases were reported. The temporal evolution of the epidemic was rapid, affecting a wide geographic area within seven weeks of the first reported cases of the season. Dengue cases were reported in 217 houses; of these 56 (25.8%) had between two and six reported cases. K-function analysis was used to characterize the spatial clustering patterns for all reported dengue cases (laboratory-positive and indeterminate) and laboratory-positive cases alone, while the Barton and David and Knox tests were used to characterize spatio-temporal attributes of dengue cases reported during the 1991-1992 outbreak. For both sets of data significant case clustering was identified within individual households over short periods of time (three days or less), but in general, the cases had spatial pattern characteristics much like the population pattern as a whole. The rapid temporal and spatial progress of the disease within the community suggests that control measures should be applied to the entire municipality, rather than to the areas immediately surrounding houses of reported cases. The potential for incorporating Geographic Information System technologies into a dengue surveillance system and the limitations of using surveillance data for spatial studies are discussed.
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                Author and article information

                Journal
                Int J Health Geogr
                International Journal of Health Geographics
                BioMed Central (London )
                1476-072X
                2006
                10 August 2006
                : 5
                : 33
                Affiliations
                [1 ]Department of Statistics, Kumaon University, S.S.J.Campus, Almora, Uttaranchal, India
                [2 ]PCI Software Pvt. Ltd., New Delhi, India
                [3 ]Community Health Centre, Sidhauli, U.P., India
                [4 ]Department of Anatomy, GSVM Medical College, Kanpur, U.P., India
                Article
                1476-072X-5-33
                10.1186/1476-072X-5-33
                1557839
                16901341
                a3314a34-6d01-4cbf-9c6a-bd428332ea63
                Copyright © 2006 Tiwari et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 June 2006
                : 10 August 2006
                Categories
                Research

                Public health
                Public health

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