| dc.description.abstract |
Peru has endured a long history with malaria, an infectious disease caused by the
mosquito-borne transmission of the Plasmodium parasite. Throughout the 20th century,
disease prevalence has varied tremendously with a number of factors including Peru’s
growth and development, variable support for malaria control measures, and the migration
of immunologically naïve populations. However, many researchers believe that anthropogenic
deforestation is at the root of a recent resurgence of malaria in the Peruvian Amazon.
Deforestation creates favorable conditions for disease transmission by increasing
mosquito habitat and placing humans in close proximity to more abundant disease vectors.
In addition, rural communities often lack the resources to combat malaria due to the
prohibitive cost of conventional technologies and lack of access to health care.
Using data derived from field collections and remotely sensed images in the Loreto
department of Peru, this study proposes a new method for characterizing malaria risk
in the Peruvian Amazon. A variety of novel geospatial and remote sensing techniques
were used to develop environmental layers from satellite imagery and produce the species
distribution model. A geospatial risk model synthesized the predicted mosquito habitat
and associated community risk factors into an assessment of malaria exposure risk.
The threat model developed from this study can be used to create maps that will help
local communities manage their malaria risk. Management efforts, such as the reduction
of available mosquito breeding habitat, can be concentrated in areas identified as
high-risk for malaria exposure.
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