INTRODUCTION: Chagas disease is a parasitosis considered a serious problem of public health. In the municipality of Barcarena, Pará, from 2007 to 2014, occurred the highest prevalence of this disease in Brazil. OBJECTIVE: To analyze the disease distribution related to epidemiological, environmental and demographic variables, in the area and period of the study. METHODS: Epidemiological and demographic data of Barcarena Health Department and satellite images from the National Institute For Space Research (INPE) were used. The deforestation data were obtained through satellite image classification, using artificial neural network. The statistical significance was done with the χ2 test, and the spatial dependence tests among the variables were done using Kernel and Moran techniques. RESULTS: The epidemiological curve indicated a disease seasonal pattern. The major percentage of the cases were in male, brown skin color, adult, illiterate, urban areas and with probable oral contamination. It was confirmed the spatial dependence of the disease cases with the different types of deforestation identified in the municipality, as well as agglomerations of cases in urban and rural areas. Discussion: The disease distribution did not occur homogeneously, possibly due to the municipality demographic dynamics, with intense migratory flows that generates the deforestation. CONCLUSION: Different relationships among the variables studied and the occurrence of the disease in the municipality were observed. The technologies used were satisfactory to construct the disease epidemiological scenarios.
INTRODUCTION: Chagas disease is a parasitosis considered a serious problem of public health. In the municipality of Barcarena, Pará, from 2007 to 2014, occurred the highest prevalence of this disease in Brazil. OBJECTIVE: To analyze the disease distribution related to epidemiological, environmental and demographic variables, in the area and period of the study. METHODS: Epidemiological and demographic data of Barcarena Health Department and satellite images from the National Institute For Space Research (INPE) were used. The deforestation data were obtained through satellite image classification, using artificial neural network. The statistical significance was done with the χ2 test, and the spatial dependence tests among the variables were done using Kernel and Moran techniques. RESULTS: The epidemiological curve indicated a disease seasonal pattern. The major percentage of the cases were in male, brown skin color, adult, illiterate, urban areas and with probable oral contamination. It was confirmed the spatial dependence of the disease cases with the different types of deforestation identified in the municipality, as well as agglomerations of cases in urban and rural areas. Discussion: The disease distribution did not occur homogeneously, possibly due to the municipality demographic dynamics, with intense migratory flows that generates the deforestation. CONCLUSION: Different relationships among the variables studied and the occurrence of the disease in the municipality were observed. The technologies used were satisfactory to construct the disease epidemiological scenarios.
Authors: José Alberto Domínguez-Alonso; David Conde-Estévez; David Bosch; Maria Pi-Figueras; Ignacio Tusquets Journal: Clin Transl Oncol Date: 2020-05-24 Impact factor: 3.405
Authors: Roberto C Ilacqua; Antônio R Medeiros-Sousa; Daniel G Ramos; Marcos T Obara; Walter Ceretti-Junior; Luis F Mucci; Mauro T Marrelli; Gabriel Z Laporta Journal: J Environ Public Health Date: 2021-07-23