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(Reference retrieved automatically from SciELO through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A method for estimating the deforestation timeline in rural settlements in a scenario of malaria transmission in frontier expansion in the Amazon Region

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Author(s):
Roberto Cardoso Ilacqua [1] ; Leonardo Suveges Moreira Chaves [2] ; Eduardo Sterlino Bergo [3] ; Jan E Conn [4, 5] ; Maria Anice Mubeb Sallum [2] ; Gabriel Zorello Laporta [6, 1]
Total Authors: 6
Affiliation:
[1] Fac Med ABC, Setor Posgrad Pesquisa & Inovacao, Santo Andre, SP - Brazil
[2] Univ Sao Paulo, Fac Saude Publ, Dept Epidemiol, Sao Paulo, SP - Brazil
[3] Secretaria Estado Saude Sao Paulo, Superintendencia Controle Endemias, Araraquara, SP - Brazil
[4] Wadsworth Ctr, New York State Dept Hlth, Slingerlands, NY - USA
[5] SUNY Albany, Dept Biomed Sci, Sch Publ Hlth, Albany, NY - USA
[6] Univ Fed ABC, Ctr Engn Modelagem & Ciencias Sociais Aplicadas, Santo Andre, SP - Brazil
Total Affiliations: 6
Document type: Journal article
Source: Memórias do Instituto Oswaldo Cruz; v. 113, n. 9 2018-07-23.
Abstract

The Malaria Frontier Hypothesis (MFH) is the current model for predicting malaria emergence in the Brazilian Amazon. It has two important dimensions, ‘settlement time’ and ‘malaria incidence’, and its prediction are: malaria incidence peaks five years after the initiation of human settlement and declines towards zero after an estimated 10 years. Although MFH is currently accepted, it has been challenged recently. Herein, we described a novel method for estimating settlement timeline by using remote sensing technology integrated in an open-software geographic information system. Surprisingly, we found that of the majority of the rural settlements with high malaria incidence are more than 10 years old. (AU)

FAPESP's process: 14/09774-1 - Dynamics of malaria transmission under distinct landscape fragmentation thresholds
Grantee:Gabriel Zorello Laporta
Support Opportunities: BIOTA-FAPESP Program - Young Investigators Grants