[Spatial distribution of endemic diseases in Ribeirão Preto, São Paulo State]. / Distribuição espacial de doenças endêmicas no município de Ribeirão Preto (SP).

The perception that some diseases happen in certain places is old. The concern in studying the relation between the human being and the environment resulted in several studies of medical geography, directed to the analysis of diseases spatial distribution. This sectional study was carried out in Ribeirão Preto, São Paulo State, and aimed to illustrate, through health problems (dengue, leprosy and tuberculosis), how a Geographic Information System tool allows the identification of heterogeneous areas, providing support for the choice of strategies and specific interventions according to the need of residents, as well as, priority of resources to more vulnerable groups. The population comprised cases of dengue, leprosy and tuberculosis notified in Ribeirão Preto in 2000. Data were collected in the Health Secretary Epidemiological Surveillance of the city. In order to obtain the thematic maps, data were geo-codified with the software MapInfo 7.8 e Spring 4.3. The thematic maps showed the density distribution of dengue, leprosy and tuberculosis cases in the city as a way to complement the analysis of health information, pointing priority areas for the control of these diseases.

Spatial distribution of leprosy cases in Ribeirão Preto, Brazil, 2004.

This cross-sectional study aimed to describe the spatial distribution of leprosy cases in Ribeirão Preto in 2004. The data collection was performed through compulsory notification records in the Epidemiological Surveillance Service of the Municipal Secretary of Health of Ribeirão Preto. The data were geo-coded through the MapInfo program version 7.8 in order to obtain the thematic map. From the 37 cases found, 62% were automatically coded, which revealed good compatibility between the database and the information in the cartographic base. The remaining 38% of the cases were geo-coded interactively. The thematic map analysis and the geo-referenced cases revealed a concentration of cases in the Northern region of the city, traditionally characterized by poor neighborhoods.