Title :
Mapping Schistosomiasis mansoni in the state of Minas Gerais, Brazil, using spatial regression
Author :
Fonseca, F.R. ; Freitas, C.C. ; Dutra, L.V.
Author_Institution :
Inst. Nac. de Pesquisas Espaciais/INPE, São José dos Campos, Brazil
Abstract :
The main goal of this paper is to develop spatial regression models to estimate the prevalence of schistosomiasis in the state of Minas Gerais, Brazil, using information on the disease spatial dependence through the network of roads and rivers, in addition to climate, socioeconomic and environmental variables. The results showed that the Schistosoma mansoni hosts mobility is an important factor for modeling and estimating the schistosomiasis prevalence distribution. Variables representing vegetation, temperature, precipitation, topography, sanitation and human development indexes, proved their importance in explaining the disease spreading, indicating favorable conditions for the disease development. The use of spatial regression showed meaningful results to the health management procedures and direction of activities, enabling a better detection of disease risk areas.
Keywords :
atmospheric precipitation; atmospheric temperature; climatology; diseases; health hazards; regression analysis; risk analysis; rivers; roads; socio-economic effects; terrain mapping; topography (Earth); vegetation; Brazil; Minas Gerais state; Schistosoma mansoni host mobility; Schistosomiasis mansoni mapping; climate variables; disease development; disease risk area detection; disease spatial dependence information; disease spreading; environmental variables; health management procedure; human development index; precipitation index; river network; road network; sanitation index; schistosomiasis prevalence distribution; schistosomiasis prevalence estimation; socioeconomic variables; spatial regression model; temperature index; topography index; vegetation index; Diseases; Humans; Indexes; Mathematical model; Rivers; Roads; Vegetation mapping; Regression analysis; schistosomiasis mansoni; spatial analysis;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
DOI :
10.1109/IGARSS.2012.6351994