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Influence of Deforestation, Logging, and Fire on Malaria in the Brazilian Amazon

Overview of attention for article published in PLOS ONE, January 2014
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Title
Influence of Deforestation, Logging, and Fire on Malaria in the Brazilian Amazon
Published in
PLOS ONE, January 2014
DOI 10.1371/journal.pone.0085725
Pubmed ID
Authors

Micah B. Hahn, Ronald E. Gangnon, Christovam Barcellos, Gregory P. Asner, Jonathan A. Patz

Abstract

Malaria is a significant public health threat in the Brazilian Amazon. Previous research has shown that deforestation creates breeding sites for the main malaria vector in Brazil, Anopheles darlingi, but the influence of selective logging, forest fires, and road construction on malaria risk has not been assessed. To understand these impacts, we constructed a negative binomial model of malaria counts at the municipality level controlling for human population and social and environmental risk factors. Both paved and unpaved roadways and fire zones in a municipality increased malaria risk. Within the timber production states where 90% of deforestation has occurred, compared with areas without selective logging, municipalities where 0-7% of the remaining forests were selectively logged had the highest malaria risk (1.72, 95% CI 1.18-2.51), and areas with higher rates of selective logging had the lowest risk (0.39, 95% CI 0.23-0.67). We show that roads, forest fires, and selective logging are previously unrecognized risk factors for malaria in the Brazilian Amazon and highlight the need for regulation and monitoring of sub-canopy forest disturbance.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 319 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 7 2%
Panama 1 <1%
Ghana 1 <1%
United Kingdom 1 <1%
Peru 1 <1%
United States 1 <1%
Madagascar 1 <1%
Unknown 306 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 16%
Student > Bachelor 45 14%
Researcher 44 14%
Student > Master 41 13%
Student > Postgraduate 20 6%
Other 73 23%
Unknown 45 14%
Readers by discipline Count As %
Environmental Science 68 21%
Agricultural and Biological Sciences 66 21%
Medicine and Dentistry 24 8%
Earth and Planetary Sciences 20 6%
Economics, Econometrics and Finance 16 5%
Other 60 19%
Unknown 65 20%