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Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, MexicoA blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.
Document ID
20040173060
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Beck, L. R.
(NASA Ames Research Center Moffett Field, CA United States)
Rodriguez, M. H.
Dister, S. W.
Rodriguez, A. D.
Washino, R. K.
Roberts, D. R.
Spanner, M. A.
Date Acquired
August 22, 2013
Publication Date
January 1, 1997
Publication Information
Publication: The American journal of tropical medicine and hygiene
Volume: 56
Issue: 1
ISSN: 0002-9637
Subject Category
Life Sciences (General)
Distribution Limits
Public
Copyright
Other

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