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Title:   Author  item
                                            Gibson, Sethitem
                                            Linthicum, Kenneth

                                                         - *Ken*item
                                            ANYAMBA, ASSAF - NASA - GODDARD SPACE FLIGitem
                                            TUCKER, COMPTON - NASA - GODDARD SPACE FLIGitem
                                            PAK, ED - NASA - GODDARD SPACE FLIGitem
                                            MALONEY, JR., FRANCIS - USACHPPM-WEST - WAitem
                                            COBB, KRISTIN - USACHPPM-SOUTH - GAitem
                                            STANWIX, ERIN - USACHPPM-SOUTH - GAitem
                                            HUMPHRIES, JERI - USACHPPM-SOUTH - GAitem
                                            SPRING, ALEXANDRA - USACHPPM-NORTH - MDitem
                                            PAGAC, BENEDICT - USACHPPM-NORTH - MDitem
                                            MILLER, MELISSA - USACHPPM-NORTH - MD
  Submitted to: Military Medicine
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 2/15/2008
                                    Publication  Date: 7/1/2008
                                    Citation: Britch, S.C., Linthicum, K., Anyamba, A., Tucker, C.J., Pak, E., Maloney, Jr., F.A., Cobb, K., Stanwix, E., Humphries, J., Spring, A., Pagac, B., Miller, M. 2008. Satellite vegetation index data as a tool to forecast population dynamics of medically important mosquitoes at military installations in the Continental United States. Military Medicine. 173(7):677-683.Interpretive Summary: A constant challenge to protecting the human population from mosquito-borne infectious diseases is controlling populations of mosquito vectors of these diseases. Civilian and military mosquito abatement agencies have good systems in place to monitor changes in mosquito populations and exert control measures accordingly -- however, it would be a strategic advantage to be able to estimate changes in mosquito populations in advance, and distribute mosquito control resources more effectively. In this study we looked at historic mosquito population surveillance data from military mosquito abatement agencies across the U.S. and found that several instances exist where population changes were preceded by key environmental changes. Environmental changes were characterized using a satellite-derived index of vegetation growth. This vegetation index may be analyzed in near real-time and serve as a platform for an automated system that could flag regions of the U.S. susceptible to unusually large populations of mosquitoes one to three months in advance. We discuss potential applications of this early warning system and its role in protecting human health across U.S. military installations.
                                Technical Abstract: The United States faces many existing and emerging mosquito-borne disease threats such as West Nile virus (WNV) and Rift Valley fever (RVF). 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 WNV, as well as possible mosquito vectors of RVF, across U.S. continental (CONUS) military installations. We compared population changes to concurrent patterns in a satellite-derived index of climate, the normalized difference vegetation index (NDVI), 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 U.S. at elevated risk of mosquito-borne disease transmission.


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