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Satellite Vegetation Index Data as a Tool to Forecast Population Dynamics of Medically Important Mosquitoes at Military Installations in the Continental United States
Author(s) -
Seth C. Britch,
Kenneth J. Linthicum,
Assaf Anyamba,
Compton J. Tucker,
Edwin W. Pak,
Francis A Maloney,
Kristin Cobb,
Erin Stanwix,
Jeri Humphries,
Alexandra Spring,
Benedict B. Pagac,
Melissa Miller
Publication year - 2008
Publication title -
military medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.442
H-Index - 67
eISSN - 1930-613X
pISSN - 0026-4075
DOI - 10.7205/milmed.173.7.677
Subject(s) - vegetation (pathology) , satellite , vegetation index , index (typography) , population , geography , meteorology , environmental science , remote sensing , climatology , medicine , environmental health , normalized difference vegetation index , ecology , climate change , biology , computer science , engineering , geology , aerospace engineering , pathology , world wide web
The United States faces many existing and emerging mosquito-borne disease threats, such as West Nile virus and Rift Valley fever. An important component of strategic prevention and control plans for these and other mosquito-borne diseases is forecasting the distribution, timing, and abundance of mosquito vector populations. Populations of many medically important mosquito species are closely tied to climate, and historical climate-population associations may be used to predict future population dynamics. Using 2003-2005 U.S. Army Center for Health Promotion and Preventive Medicine mosquito surveillance data, we looked at populations of several known mosquito vectors of West Nile virus, as well as possible mosquito vectors of Rift Valley fever virus, at continental U.S. military installations. We compared population changes with concurrent patterns for a satellite-derived index of climate (normalized difference vegetation index) and observed instances of population changes appearing to be direct responses to climate. These preliminary findings are important first steps in developing an automated, climate-driven, early warning system to flag regions of the United States at elevated risk of mosquito-borne disease transmission.

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