A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil.
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 (R(2) = 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 (R(2) = 0.97), 2 (R(2) = 0.60), 3 (R(2) = 0.63) and 4 (R(2) = 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.
Guimarães
Ricardo José de Paula Souza
RJ
Instituto de Pesquisas René Rachou, Fiocruz, Belo Horizonte, MG, Brasil.
Freitas
Corina Costa
CC
Dutra
Luciano Vieira
LV
Scholte
Ronaldo Guilherme Carvalho
RG
Martins-Bedé
Flávia Toledo
FT
Fonseca
Fernanda Rodrigues
FR
Amaral
Ronaldo Santos
RS
Drummond
Sandra Costa
SC
Felgueiras
Carlos Alberto
CA
Oliveira
Guilherme Corrêa
GC
Carvalho
Omar Santos
OS
D000818:Animals; D001700:Biomphalaria; D001938:Brazil / Q000453:epidemiology; D004199:Disease Vectors; D040362:Geographic Information Systems; D006801:Humans; D016014:Linear Models; D015995:Prevalence; D018570:Risk Assessment; D012552:Schistosomiasis / Q000453:epidemiology / Q000517:prevention & control*; D012621:Seasons