ArticleMemorias do Instituto Oswaldo Cruz2018
A method for estimating the deforestation timeline in rural settlements in a scenario of malaria transmission in frontier expansion in the Amazon Region.
Article in Memorias do Instituto Oswaldo Cruz, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Human occupation, not forest structure, determines sand fly abundance in the Amazon.Parasites & vectors · 2026Article
- Deforestation and human proximity influence Trypanosoma cruzi infection in palm-dwelling triatomines.PloS one · 2026Article
- Zoonotic Malaria Risk in Serra Do Mar, Atlantic Forest, Brazil.Microorganisms · 2023Article
- Malaria transmission in landscapes with varying deforestation levels and timelines in the Amazon: a longitudinal spatiotemporal study.Scientific reports · 2021Article
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- Article
- Reemergence of Yellow Fever in Brazil: The Role of Distinct Landscape Fragmentation Thresholds.Journal of environmental and public health · 2021Article
- A Retrospective Survey of Rodent-borne Viruses in Rural Populations of Brazilian Amazon.Revista da Sociedade Brasileira de Medicina Tropical · 2020Article
- Comparison of malaria incidence rates and socioeconomic-environmental factors between the states of Acre and Rondônia: a spatio-temporal modelling study.Malaria journal · 2019Article
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Authors and funding
6 authors.
Funding
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.
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