A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

• Main Authors: Ricardo José de Paula Souza Guimarães, Corina Costa Freitas, Luciano Vieira Dutra, Ronaldo Guilherme Carvalho Scholte, Flávia Toledo Martins-Bedé, Fernanda Rodrigues Fonseca, Ronaldo Santos Amaral, Sandra Costa Drummond, Carlos Alberto Felgueiras, Guilherme Corrêa Oliveira, Omar Santos Carvalho
• Format: Article
• Language: English
• Published: Instituto Oswaldo Cruz, Ministério da Saúde 2010-07-01
• Series: Memórias do Instituto Oswaldo Cruz.
• Subjects: schistosomiasis; geographical information system; geostatistical procedures; Biomphalaria; multiple linear regression; epidemiology
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762010000400030

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.