Aplicação do geoprocessamento na análise espacial da Leishmaniose Tegumentar Americana e suas consequências socioambientais no município de Augusto Corrêa-PA - SOARES, Ney Leonardo Silva (2019)
American Tegumentary Leishmaniasis (LTA) is an infectious and parasitic anthropozoonosis caused by a protozoan of the genus Leishmania, with vector transmission, with hosts of wild, synanthropic and domestic animals. The vector are insects called phlebotomines commonly known as mosquito "straw", "tatuquira", "birigui". The LTA mainly affects people who have direct contact with the forest and rural areas without due protection because they are endemic areas of this disease, because they present sites favorable to its appearance, with the growth of the agricultural frontier and Deforestation, LTA cases become increasingly common in rural areas and in areas of vegetable and mineral extraction, Augusto Corrêa was located in the northeastern region of the state of Pará, where data were collected from the years 2007 to 2017, in order to it is necessary to perform a spatial analysis of the cases and to understand the dynamics of this problem through geoprocessing tools. The municipality stands out for presenting relevant numbers of cases notified in the State, because it presents many epidemiological characteristics of the disease, such conditions can be understood when the appropriate use of the geotechnologies allows the understanding of its casuistry in the environment. The data source used was: SINAN 2007-2017, IBGE 2010, INPE 2014. In addition to data collected in the field using the Global Positioning System (GPS). Already the processing and interpretation of the spatial data was carried out with the software ArcGIS 10.5.1, where the data in Excel format was inserted. 109 cases were georeferenced in the municipality of Augusto Corrêa from 2007 to 2017, and spatialized, subsidizing the understanding of the behavior of infections and their aggravations in the local and regional socio-environmental context. As for example the combinations of the spatialization of the number of cases with data of census sector where it shows the resident population with the number of cases, besides the density of Kernel that allows the visualization of agglomerates.