The geographic information system approach has permitted integration between demographic, socio-economic and environmental data, providing correlation between information from several data banks. In the current work, occurrence of human and canine visceral leishmaniases and insect vectors (Lutzomyia longipalpis) as well as biogeographic information related to 9 areas that comprise the city of Belo Horizonte, Brazil, between April 2001 and March 2002 were correlated and georeferenced. By using this technique it was possible to define concentration loci of canine leishmaniasis in the following regions: East; Northeast; Northwest; West; and Venda Nova. However, as for human leishmaniasis, it was not possible to perform the same analysis. Data analysis has also shown that 84.2% of the human leishmaniasis cases were related with canine leishmaniasis cases. Concerning biogeographic (altitude, area of vegetation influence, hydrographic, and areas of poverty) analysis, only altitude showed to influence emergence of leishmaniasis cases. A number of 4673 canine leishmaniasis cases and 64 human leishmaniasis cases were georeferenced, of which 67.5 and 71.9%, respectively, were living between 780 and 880 m above the sea level. At these same altitudes, a large number of phlebotomine sand flies were collected. Therefore, we suggest control measures for leishmaniasis in the city of Belo Horizonte, giving priority to canine leishmaniasis foci and regions at altitudes between 780 and 880 m.

From the mapping of urban vegetation cover by high-resolution orthoimages, using IR band and NDVI classification (Normalized Difference Vegetation Index), added to three-dimensional representation obtained by LiDAR capture (Light Detection and Ranging), the volumetric values of vegetal cover are obtained as a base to construct spatial analysis in the district of Pampulha, in Belo Horizonte, investigating the role it plays in the neighborhood. The article aims to analyze the relationship between vegetation cover, income distribution and population density, as a support to urban environmental quality management. It applies Exploratory Spatial Data Analysis (ESDA) to identify the presence of clusters and patterns of spatial distribution and to examine spatial autocorrelation. The results confirm the concentration of vegetation cover in areas of high income and lower population density but the main contribution of the study is the use of a method to analyze the spatial behavior of this distribution. Calculating Moran global index and local index (LISA), these spatial combinations are mainly used to identify transformation pressures, which may result in the definition of priorities for public actions and the construction of proposals for parameterization of vegetation cover to support plans related to green infrastructure in urban areas.

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Resumo O objetivo foi analisar a distribuição espacial da fragilidade em idosos na atenção primária à saúde identificando espacialmente áreas com concentração de idosos comparando a demanda por atendimento. Estudo analítico que utilizou análise espacial com idosos frágeis ou em risco de fragilização cadastrados na Atenção Primária à Saúde, distribuídos em 32 setores censitários. Para geolocalização utilizou-se software Google Earth Pro e “app C7 GPS Dados”, para elaboração dos mapas temático e cadastral o Qgis 2.16. Classificou-se em risco de fragilização 43% dos idosos, sendo 79,5% do sexo feminino, com média de idade 75 anos. A organização dos serviços apresentou distribuição desigual das unidades no território, com os três cenários de atenção à saúde presentes ou não em alguns setores, e concentração de idosos onde os serviços tinham difícil acesso. A análise espacial apontou a distribuição e áreas de concentração da fragilidade, favorecendo a comparação da vulnerabilidade social com a potencialidade de atendimento por parte dos serviços de saúde, dando suporte a ações de planejamento e gestão de distribuição de unidades ou projetos de visita aos necessitados. Assim, as ferramentas de geoinformação são potenciais ao fortalecimento do acesso a serviços de saúde e melhores condições de vida do idoso.