Please use this identifier to cite or link to this item:
Title: Understanding the disease vector operational environment by predicting presence of Anopheles mosquito breeding sites using maximum entropy modeling and the Maxent software platform
Authors: Lyon, Susan L.
Payne, Kathleen V.
Keywords: Mosquitoes as carriers of disease
Diseases--Risk factors
Maximum entropy method
Publisher: Geospatial Research Laboratory (U.S.)
Engineer Research and Development Center (U.S.)
Series/Report no.: Technical Note (Engineer Research and Development Center (U.S.)) ; no. ERDC/GRL TN-20-5
Abstract: This technical note (TN) describes research using the maximum entropy model to predict the presence of breeding sites for mosquitos of the genus Anopheles throughout the Korean peninsula. This methodology is also applicable to many other types of ecological niche modeling problems where analysts only have access to data related to the location a species has been found. The purpose of this study is to help address the need for new and innovative methods that promote military readiness through better understanding of vector-borne disease threats in familiar and unfamiliar operational environments. These methods can be used to provide military planners with valuable information to support their operations, particularly when operations expand into areas lacking direct disease vector surveillance. Disease vector risk information is vital for force readiness, because historically, soldiers are more likely to be unable to perform warfighting due to disease and non-combat injuries than as a direct result of combat (U.S. Department of the Army 2015).
Description: Technical Note
Gov't Doc #: ERDC/GRL TN-20-5
Rights: Approved for Public Release; Distribution is Unlimited
Size: 8 pages / 1.64 MB
Types of Materials: PDF
Appears in Collections:Technical Note

Files in This Item:
File Description SizeFormat 
ERDC-GRL TN-20-5.pdf1.64 MBAdobe PDFThumbnail