Risk mapping of the schistosomiasis in the minas gerais state, brazil, using modis and socioeconomic spatial data

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 1, Issue 1, 2008, Pages

  De Toledo Martins, Flávia ^a   Da Costa Freitas, Corina ^a   Dutra, Luciano Vieira ^a   Fonseca, Fernanda Rodrigues ^a   De Paula Souza e Guimaraes, Ricardo José ^b,c   Do Amaral, Ronaldo Santos ^d   Moura, Ana Clara Mourao ^e   Carvalho, Omar Dos Santos ^b  

^a INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS   (Brazil)

^b INSTITUTO OSWALDO CRUZ   (Brazil)

^c Programa de Pós Graduação da Santa Casa de Misericórdia de Belo Horizonte   (Brazil)

^d Secretaria de Vigilância em Saúde   (Brazil)

^e FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

Author keywords

GIS; Regression models; Remote Sensing; Schistosomiasis

Indexed keywords

BEHAVIORAL CHARACTERISTICS; DISEASE RISKS; GIS; MINAS GERAIS; REGRESSION MODEL; REGRESSION MODELS; SCHISTOSOMIASIS; SPATIAL DATA;

GEOGRAPHIC INFORMATION SYSTEMS; REGRESSION ANALYSIS; REMOTE SENSING;

RISK PERCEPTION;

EID: 67649810229     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2008.4778845     Document Type: Conference Paper

References (3)

1. F.F. Feitosa, G. Câmara, A.M.V. Monteiro, T. Koschitzi, M.P.S. Silva, "Global and local spatial indices of urban segregation" International Journal of Geographical Science, Taylor & Francis, vol 21(3): 299-323, March 2007.
2. C.C. Freitas, R.J.D.P.S. Guimarães, L.V. Dutra, F.T. Martins, É.J.C. Gouvêa, R.A.T. Santos, A.C.D.M. Moura, S.C. Drummond, R.S. Amaral, O.D.S. Carvalho, "Remote Sensing and Geographic Information Systems for the Study of Schistosomiasis in the state of Minas Gerais, Brazil". IEEE International Geoscience And Remote Sensing Symposium, Denver, CO, USA p. 2436-2439, jul./ago. 2006.
3. R.J.D.P.S. Guimarães, C.C. Freitas, L.V. Dutra, A.C.D.M. Moura, R.S. Amaral, S.C. Drummond, R.G. Scholte, C.R. Freitas, O.D.S. Carvalho, "Analysis and estimative of schistosomiasis prevalence for Minas Gerais state, Brazil, using multiple regression with social and environmental spatial data", Mem Inst Oswaldo Cruz, Scielo, Rio de Janeiro, Vol. 101(Suppl. I): 91-96, 2006.