Your browser doesn't support javascript.
loading
The Estrada Real project and endemic diseases: the case of schistosomiasis, geoprocessing and tourism
Carvalho, Omar S; Scholte, Ronaldo GC; Guimarães, Ricardo JPS; Freitas, Corina C; Drummond, Sandra C; Amaral, Ronaldo S; Dutra, Luciano V; Oliveira, Guilherme; Massara, Cristiano L; Enk, Martin J.
Affiliation
  • Carvalho, Omar S; Laboratório de Helmintologia e Malacologia Médica. BR
  • Scholte, Ronaldo GC; Laboratório de Helmintologia e Malacologia Médica. BR
  • Guimarães, Ricardo JPS; Laboratório de Helmintologia e Malacologia Médica. BR
  • Freitas, Corina C; Instituto Nacional de Pesquisas Espaciais. São José dos Campos. BR
  • Drummond, Sandra C; Secretaria de Estado de Saúde de Minas Gerais. Belo Horizonte. BR
  • Amaral, Ronaldo S; Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília. BR
  • Dutra, Luciano V; Instituto Nacional de Pesquisas Espaciais. São José dos Campos. BR
  • Oliveira, Guilherme; Instituto de Pesquisas René Rachou-Fiocruz. Laboratório de Parasitologia Celular e Molecular. Belo Horizonte. BR
  • Massara, Cristiano L; Laboratório de Helmintologia e Malacologia Médica. BR
  • Enk, Martin J; Laboratório de Esquistossomose. BR
Mem. Inst. Oswaldo Cruz ; 105(4): 532-536, July 2010. ilus
Article in En | LILACS | ID: lil-554826
Responsible library: BR1.1
ABSTRACT
Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R² = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.
Subject(s)
Key words
Full text: 1 Index: LILACS Main subject: Schistosomiasis / Travel / Endemic Diseases / Geographic Information Systems Type of study: Etiology_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Country/Region as subject: America do sul / Brasil Language: En Journal: Mem. Inst. Oswaldo Cruz Journal subject: MEDICINA TROPICAL / PARASITOLOGIA Year: 2010 Type: Article / Project document
Full text: 1 Index: LILACS Main subject: Schistosomiasis / Travel / Endemic Diseases / Geographic Information Systems Type of study: Etiology_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Country/Region as subject: America do sul / Brasil Language: En Journal: Mem. Inst. Oswaldo Cruz Journal subject: MEDICINA TROPICAL / PARASITOLOGIA Year: 2010 Type: Article / Project document