D Gómez-Barroso1, E Rodriguez-Valín, R Ramis, R Cano. 1. Consorcio de Investigación Biomédica en Red en Epidemiología y Salud Pública, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain. dgomez@isciii.es
Abstract
BACKGROUND: The characteristics of respiratory tuberculosis (TB) favour the appearance of clusters of cases in space and time. It is important for public health authorities to know which clusters occur randomly and which merit further investigation. OBJECTIVE: To detect spatial and spatio-temporal clusters of respiratory TB in Spain during the period from 1 January 2008 to 31 December 2010. MATERIALS AND METHODS: Retrospective spatio-temporal study of respiratory TB cases reported to Spain's National Epidemiological Surveillance Network from 2008 to 2010, at a municipal level. We used the purely spatial and space-time Scan statistic estimators. All analyses were adjusted for age and sex. RESULTS: The spatial cluster analysis detected 28 significant clusters and the spatio-temporal cluster analysis detected 20 significant clusters. The most likely spatial cluster comprised seven municipalities in the Greater Barcelona Area. Most space-time clusters were situated in the same area, and were detected between 1 April 2008 and 31 March 2009. CONCLUSION: The distribution of TB clusters as shown by the proposed models furnishes a spatial pattern of the distribution of the disease. The two methods used can be a useful tool for analysing the distribution of respiratory TB in Spain.
BACKGROUND: The characteristics of respiratory tuberculosis (TB) favour the appearance of clusters of cases in space and time. It is important for public health authorities to know which clusters occur randomly and which merit further investigation. OBJECTIVE: To detect spatial and spatio-temporal clusters of respiratory TB in Spain during the period from 1 January 2008 to 31 December 2010. MATERIALS AND METHODS: Retrospective spatio-temporal study of respiratory TB cases reported to Spain's National Epidemiological Surveillance Network from 2008 to 2010, at a municipal level. We used the purely spatial and space-time Scan statistic estimators. All analyses were adjusted for age and sex. RESULTS: The spatial cluster analysis detected 28 significant clusters and the spatio-temporal cluster analysis detected 20 significant clusters. The most likely spatial cluster comprised seven municipalities in the Greater Barcelona Area. Most space-time clusters were situated in the same area, and were detected between 1 April 2008 and 31 March 2009. CONCLUSION: The distribution of TB clusters as shown by the proposed models furnishes a spatial pattern of the distribution of the disease. The two methods used can be a useful tool for analysing the distribution of respiratory TB in Spain.
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