Geoprocessing in monitoring of tuberculosis in state of São Paulo

• Grant number: 13/10305-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: August 01, 2013
• End date: July 31, 2014
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Luiz Fernando Costa Nascimento
• Grantee: Taís Siqueira Venâncio
• Host Institution: Instituto Básico de Biociências (IBB). Universidade de Taubaté (UNITAU). Taubaté , SP, Brazil

Abstract

Tuberculosis is a chronic infectious disease that has long affected humanity. The first written record dates from about 700 BC. Aristotle was the first person who described the contagious nature of the disease. As the constant urbanization occurred during the past century, the incidence has greatly increased and became the 4th leading cause of death in adults in Europe. The incidence of tuberculosis in Brazil is 50 cases per 100,000 inhabitants. In São Paulo the incidence is 38 cases / 100,000 inhabitants in 2009. Disease mapping has been a basic instrument in the public health's field and, in recent years, many advances in analytical techniques have been developed in order to produce maps which construction must be free of "random noise" or artifacts related to the geographical area extension and the current population in the focused regions; In conclusion of this thought, several studies have been developed in Brazil. The goal of this project is to identify spatial patterns of tuberculosis incidence in the municipalities of the state of São Paulo in two periods: 2001-2005 and 2006-2010. The data on the incidence of tuberculosis will be obtained from the CVE and inserted into the program TerraView. The spatial auto-correlation rates of tuberculosis are estimated using the global Moran index, which ranges between -1 and 1. It is going to be built thematic maps with these rates and with the values of the local Moran index that identifies counties where intervention should be performed. It's expected to identify clusters of counties with high rates and municipalities with high priority of intervention. (AU)