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      Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

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          Abstract

          Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters ( P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City.

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          Tuberculosis

          Tuberculosis results in an estimated 1·7 million deaths each year and the worldwide number of new cases (more than 9 million) is higher than at any other time in history. 22 low-income and middle-income countries account for more than 80% of the active cases in the world. Due to the devastating effect of HIV on susceptibility to tuberculosis, sub-Saharan Africa has been disproportionately affected and accounts for four of every five cases of HIV-associated tuberculosis. In many regions highly endemic for tuberculosis, diagnosis continues to rely on century-old sputum microscopy; there is no vaccine with adequate effectiveness and tuberculosis treatment regimens are protracted and have a risk of toxic effects. Increasing rates of drug-resistant tuberculosis in eastern Europe, Asia, and sub-Saharan Africa now threaten to undermine the gains made by worldwide tuberculosis control programmes. Moreover, our fundamental understanding of the pathogenesis of this disease is inadequate. However, increased investment has allowed basic science and translational and applied research to produce new data, leading to promising progress in the development of improved tuberculosis diagnostics, biomarkers of disease activity, drugs, and vaccines. The growing scientific momentum must be accompanied by much greater investment and political commitment to meet this huge persisting challenge to public health. Our Seminar presents current perspectives on the scale of the epidemic, the pathogen and the host response, present and emerging methods for disease control (including diagnostics, drugs, biomarkers, and vaccines), and the ongoing challenge of tuberculosis control in adults in the 21st century. Copyright © 2011 Elsevier Ltd. All rights reserved.
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            Multivariate scan statistics for disease surveillance.

            In disease surveillance, there are often many different data sets or data groupings for which we wish to do surveillance. If each data set is analysed separately rather than combined, the statistical power to detect an outbreak that is present in all data sets may suffer due to low numbers in each. On the other hand, if the data sets are added by taking the sum of the counts, then a signal that is primarily present in one data set may be hidden due to random noise in the other data sets. In this paper, we present an extension of the spatial and space-time scan statistic that simultaneously incorporates multiple data sets into a single likelihood function, so that a signal is generated whether it occurs in only one or in multiple data sets. This is done by defining the combined log likelihood as the sum of the individual log likelihoods for those data sets for which the observed case count is more than the expected. We also present another extension, where the concept of combining likelihoods from different data sets is used to adjust for covariates. Using data from the National Bioterrorism Syndromic Surveillance Demonstration Project, we illustrate the new method using physician telephone calls, regular physician visits and urgent care visits by Harvard Pilgrim Health Care members cared for by Harvard Vanguard Medical Associates, a large multi-specialty group practice in Massachusetts. For upper and lower gastrointestinal (GI) illness, there were on average 20 telephone calls, nine urgent care visits and 22 regular physician visits per day. The strongest signal was generated by a single data set and due to a familial outbreak of pinworm disease. The second and third strongest signals were generated by the combined strength of two of the three data sets. c 2007 John Wiley & Sons, Ltd.
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              Is Open Access

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

              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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                Author and article information

                Journal
                ScientificWorldJournal
                ScientificWorldJournal
                TSWJ
                The Scientific World Journal
                The Scientific World Journal
                1537-744X
                2012
                31 July 2012
                : 2012
                : 570278
                Affiliations
                1Facultad de Medicina, Universidad Autónoma del Estado de México, 50180, Toluca, MEX, Mexico
                2Centro Interamericano de Recursos del Agua, Universidad Autónoma del Estado de México, 50200, Toluca, MEX, Mexico
                3Facultad de Medicina Veterinaria Zootécnia, Universidad Autónoma del Estado de México, 50200, Toluca, MEX, Mexico
                4Departamento de Producción Agrícola y Animal, Universidad Autónoma Metropolitana, 04960, México, DF, Mexico
                Author notes
                *Ninfa Ramírez Durán: nramirezd@ 123456uaemex.mx

                Academic Editors: K. Akakura, P. Domingo, and Q. He

                Article
                10.1100/2012/570278
                3417174
                22919337
                ba3d14f1-65a1-42fd-8997-d6bdbc9966ff
                Copyright © 2012 Adrian Zaragoza Bastida et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 April 2012
                : 29 May 2012
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