Spatiotemporal-based clusters as a method for dengue surveillance/ Uso de conglomerados basados en el tiempo y el espacio como metodo de vigilancia del dengue/ Conglomerados espacotemporais como metodo de vigilancia da dengue.(Original research texto en ingles)

Objectives. To develop and demonstrate the use of a new method for epidemiological surveillance of dengue. Methods. This was a retrospective cohort study using data from the Health Department of Sao Jose do Rio Preto (Sao Paulo, Brazil). The geographical coordinates were obtained using QGIS[TM] (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan[TM] (Martin Kulldorff, Boston, Massachusetts, United States) was then used to create a space-time scan analysis to find statistically significant clusters of dengue. These results were plotted and visualized using Google Earth[TM] mapping service (Google Incorporated, Mountain View, California, United States). Results. More clusters were detected when the maximum number of households per cluster was set to 10% (11 statistically significant clusters) rather than 50% (8 statistically significant clusters). The cluster radius varied from 0.18-2.04 km and the period of time varied from 6 days--6 months. The infection rate was more than 0.5 cases/household. Conclusions. When using SaTScan for space-time analysis of dengue cases, the maximum number of households per cluster should be set to 10%. This methodology may be useful to optimizing dengue surveillance systems, especially in countries where resources are scarce and government programs have not had much success controlling the disease. Keywords Geographic information systems; dengue; public health surveillance; communicable diseases, emerging; Brazil. Objetivos. Elaborar un metodo nuevo para la vigilancia epidemiologica del dengue y hacer una demostracion sobre su uso. Metodos. Se realizo un estudio retrospectivo de cohortes usando datos del Departamento de Salud de Sao Jose do Rio Preto (Sao Paulo, Brasil). Partiendo de la direccion de los pacientes en el sistema de notificacion del dengue del Gobierno de Brasil, se uso QGIS[TM] (Creative Commons Corporation, Mountain View, California, Estados Unidos) para obtener sus coordenadas geograficas. Luego se uso SaTScan[TM] (Martin Kulldorff, Boston, Massachusetts, Estados Unidos) para crear un analisis de exploracion espacio-temporal a fin de detectar conglomerados de dengue estadisticamente significativos. Por ultimo, se uso el servicio de mapas de Google Earth[TM] (Google Incorporated, Mountain View, California, Estados Unidos) para graficar y visualizar estos resultados. Resultados. Se detectaron ma