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

Roberto Cardoso Ilacqua,Leonardo Suveges Moreira Chaves,Gabriel Zorello Laporta,Eduardo Sterlino Bergo,Maria Anice Mubeb Sallum,Jan E Conn

doi:10.1590/0074-02760170522

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.

Highlights

Malaria was in the elimination phase in some endemic areas of the Amazon River Basin until 2017, when it re-emerged as a significant threat.[1]. This disease is a continuous threat to public health, especially in municipalities where the control program has been either reduced or discontinued for any length of time
This re-emergence scenario is more challenging because the potential for malaria transmission usually remains high due to environmental, social and economic determinants in the Amazon that favour the occurrence of the mosquito vectors and Plasmodium transmission
Malaria Frontier Hypothesis (MFH) can be a poor predictor of the dynamics of malaria transmission in the Amazon

Summary

Introduction

Malaria was in the elimination phase in some endemic areas of the Amazon River Basin until 2017, when it re-emerged as a significant threat.[1]. In contrast to the MFH, studies by Barros et al[7] and Barros and Honório[8] found that old settlements are or more likely to have high malaria incidence (e.g., high parasite index) compared with a region that was recently inhabited. In this study we propose a method for estimating deforestation that addresses the potential association between the degree of deforestation and malaria incidence in rural settlements in the Amazon.

Results

Conclusion