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Our Integrated System Solutions proposal for Public Health Applications describes the incorporation of NASA models and remote sensing data into a risk assessment model that coalesces environmental, mosquito abundance, and encephalitis virus measurements from the California Mosquito-borne Virus Surveillance and Response Plan (CMVSRP) and the Arbovirus Surveillance Network (ArboNET). The CMVSRP is a decision support system (DSS) currently used by the California Department of Health Services (CDHS) and 53 mosquito and vector control districts (MVCDs) to make intervention decisions regarding West Nile (WNV), St. Louis encephalitis (SLEV) and western equine encephalomyelitis (WEEV) viruses. Data on eight environmental and epidemiological factors are ranked and averaged within the CMVSRP model to produce a real-time estimate of virus risk. CMVSRP users rely on these estimates to make management decisions on pesticide applications for vector control, funding and effort levels for public education and media outreach, and coordination with physicians and emergency services personnel. Within the CMVSRP, the current system used to rank climate variation is not integrated well with mosquito and virus surveillance data. ArboNET is a national reporting and information system operated by the Centers for Disease Control and Prevention (CDC) to document and visualize arbovirus activity reported by state and local health departments. Users include state and local health departments nationwide who rely on ArboNET, in combination with other data sources, to make management decisions related to the initiation of public outreach and media campaigns to encourage the use of preventative measures that may reduce the risk of mosquitoborne virus transmission. We propose to focus initial efforts on enhancing the CMVSRP by effectively integrating NASA models and real-time remote sensing data to accurately define and map current and future mosquito activity and virus transmission risk. Mosquito abundance and risk forecasts based on remote sensing data and validated at a regional scale are likely to be extrapolative to the western United States. Forecasting skill will be evaluated and improved through retrospective simulations using data gathered by ArboNET. Once adequate forecasting skill is developed, our system may be integrated into the suite of maps available through the CDC WN website to enhance current decision support systems for tracking vector-borne diseases. The integrated DSS will be a model system for the application of NASA products for monitoring and management of vectors and vector-borne diseases, including those new agents which may be introduced inadvertently or purposefully into the U.S.