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.
Yellow Fever Virus (YFV) reemergence in Brazil was followed by human suffering and the loss of biodiversity of neotropical simians on the Atlantic coast. The underlying mechanisms were investigated with special focus on distinct landscape fragmentation thresholds in the affected municipalities. An ecological study in epidemiology is employed to assess the statistical relationship between events of YFV and forest fragmentation in municipal landscapes. Negative binomial regression model showed that highly fragmented forest cover was associated with an 85% increase of events of YFV in humans and simians (RR = 1.85, CI 95% = 1.24–2.75,
p
=
0.003
) adjusted by vaccine coverage, population size, and municipality area. Intermediate levels of forest cover combined with higher levels of forest edge densities contribute to the YFV dispersion and the exponential growth of YF cases. Strategies for forest conservation are necessary for the control and prevention of YF and other zoonotic diseases that can spillover from the fragmented forest remains to populated cities of the Brazilian Atlantic coast.
The relationship between deforestation and malaria is a spatiotemporal process of variation in Plasmodium incidence in human-dominated Amazonian rural environments. The present study aimed to assess the underlying mechanisms of malarial exposure risk at a fine scale in 5-km2 sites across the Brazilian Amazon, using field-collected data with a longitudinal spatiotemporally structured approach. Anopheline mosquitoes were sampled from 80 sites to investigate the Plasmodium infection rate in mosquito communities and to estimate the malaria exposure risk in rural landscapes. The remaining amount of forest cover (accumulated deforestation) and the deforestation timeline were estimated in each site to represent the main parameters of both the frontier malaria hypothesis and an alternate scenario, the deforestation-malaria hypothesis, proposed herein. The maximum frequency of pathogenic sites occurred at the intermediate forest cover level (50% of accumulated deforestation) at two temporal deforestation peaks, e.g., 10 and 35 years after the beginning of the organization of a settlement. The incidence density of infected anophelines in sites where the original forest cover decreased by more than 50% in the first 25 years of settlement development was at least twice as high as the incidence density calculated for the other sites studied (adjusted incidence density ratio = 2.25; 95% CI, 1.38–3.68; p = 0.001). The results of this study support the frontier malaria as a unifying hypothesis for explaining malaria emergence and for designing specific control interventions in the Brazilian Amazon.
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