Satellite vegetation index data as a tool to forecast population dynamics of medically important mosquitoes at military installations in the continental United States.
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.
Britch
Seth C
SC
U.S. Department of Agriculture, Agricultural Research Service, Center for Medical, Agricultural, and Veterinary Entomology, Gainesville, FL 32608, USA.
Linthicum
Kenneth J
KJ
Anyamba
Assaf
A
Tucker
Compton J
CJ
Pak
Edwin W
EW
Maloney
Francis A
FA
Cobb
Kristin
K
Stanwix
Erin
E
Humphries
Jeri
J
Spring
Alexandra
A
Pagac
Benedict
B
Miller
Melissa
M
D000818:Animals; D002980:Climate; D009033:Culicidae; D005260:Female; D006801:Humans; D007303:Insect Vectors; D008887:Military Medicine; D008889:Military Personnel; D009032:Mosquito Control; D010944:Plants; D011157:Population Dynamics; D011159:Population Surveillance; D036301:Qualitative Research; D011891:Rain; D012307:Risk Factors; D018531:Spacecraft; D014481:United States