Predictions of Malaria Vector Distribution in Belize Based on Multispectral Satellite Data

Donald R. Roberts Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Jack F. Paris Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Sylvie Manguin Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Ralph E. Harbach Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Robert Woodruff Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Eliska Rejmankova Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Jorge Polanco Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Bruce Wullschleger Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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Llewellyn J. Legters Department of Preventive Medicine/Biometrics, Uniformed Services University of the Health Sciences, GeoInformation Technology, California State University, Department of Entomology, The Natural History Museum, Division of Environmental Studies, University of California, Malaria Control, Ministry of Health, Bethesda, Maryland, United Kingdom

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DOI:
https://doi.org/10.4269/ajtmh.1996.54.304
Volume/Issue:
Volume 54: Issue 3
Page(s):
304–308
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Use of multispectral satellite data to predict arthropod-borne disease trouble spots is dependent on clear understandings of environmental factors that determine the presence of disease vectors. A blind test of remote sensing-based predictions for the spatial distribution of a malaria vector, Anopheles pseudopunctipennis, was conducted as a follow-up to two years of studies on vector-environmental relationships in Belize. Four of eight sites that were predicted to be high probability locations for presence of An. pseudopunctipennis were positive and all low probability sites (0 of 12) were negative. The absence of An. pseudopunctipennis at four high probability locations probably reflects the low densities that seem to characterize field populations of this species, i.e., the population densities were below the threshold of our sampling effort. Another important malaria vector, An. darlingi, was also present at all high probability sites and absent at all low probability sites. Anopheles darlingi, like An. pseudopunctipennis, is a riverine species. Prior to these collections at ecologically defined locations, this species was last detected in Belize in 1946.

Author Notes

Copyright:
Copyright © 1996 by The American Society of Tropical Medicine and Hygiene 1996
Published Online:
Mar 1996
Cover The American Journal of Tropical Medicine and Hygiene
The American Journal of Tropical Medicine and Hygiene
Print ISSN:
0002-9637
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