Distribuição espacial dos casos de hanseníase em um município do interior do Estado de São Paulo, 2006-2016

• Ano de defesa: 2019
• Autor(a) principal: Roveroni, Ana Paula
• Orientador(a): Protti-Zanatta, Simone Teresinha
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Enfermagem - PPGEnf
• Palavras-chave em Português: Análise espacial; Atenção Primária à Saúde; Hanseníase; Sistemas de Informação em Saúde
• Palavras-chave em Inglês: Spatial analysis; Primary Health Care; Leprosy; Health Information Systems
• Palavras-chave em Espanhol: Análisis espacial; Atención Primaria a la Salud; La lepra; Sistemas de Información en Salud
• Área do conhecimento CNPq: CIENCIAS DA SAUDE::ENFERMAGEM::ENFERMAGEM DE SAUDE PUBLICA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/13285

Objective:To analyze spatial and spatial-temporal risk areas for the occurrence of leprosy in the municipality of Araras, State of São Paulo. Materials and Methods:This is a descriptive and ecological study of leprosy cases registered in the Health Information System of the Ministry of Health between 2006 and 2016.At the stage of the exploratory analysis of the data, we used the analysis using software R (version 3.5.1), where calculations of central tendency measurements were performed for continuous variables, absolute and relative frequencies for categorical variables. For the spatial analysis only the cases with registered addresses were considered, being the same geocoded. It was applied to the Kernel density statistic to identify the areas of higher density and the scanning statistic for identification of clusters of risk. In the analyzes were used the software ArcGIS (version 10.6), Google Earth and SaTScan (version 9.4). The study was submitted and approved by the Research Ethics Committee of the Federal University of São Carlos (UFSCar), under opinion nº 2.495.187. Results:85 cases of leprosy were identified, with a predominance of cases in males, with an age equal to or greater than 51 years, white race, with complete or incomplete primary education and with a dimorphic clinical form. 75 (88.2%) cases were geocoded. In Kernel analysis it was possible to observe a heterogeneous spatial distribution of the disease in the municipality. In the face of the scanning analysis, two statistically significant areas of risk were identified, being considered one of high risk (RR=3.47;CI95%:2.15-5.58;p=0.002). In relation to the space-time analysis, a statistically significant risk area was identified, being a high risk, considering a cluster in the period from 2009 to 2012 (RR=6.22; CI95%: 3.66-10.56; p=0.000). The areas most affected by leprosy have low income populations living in poverty and extreme poverty. Conclusion:The study made it possible to reveal the spatial distribution of leprosy and to identify areas of greater and lesser spatial and spatial-temporal risk for the occurrence of this disease from the application of statistical analyzes, in which they contributed to the knowledge of the dynamics of the disease, given the characteristics of the space considered an essential tool in the control and monitoring of leprosy. However, recognition of these areas may provide, in accordance with local priorities and needs, subsidies in the implementation of social protection strategies, applicability of financial resources and actions in health for the effective control of the disease