REAL-TIME WATERFOWL MAPPING WEB APP: A CRITICAL & NOVEL TOOL FOR AVIAN INFLUENZA SURVEILLANCE TO IMPROVE FOOD SECURITY IN COMMERCIAL POULTRY

This proposal aims to develop and validate a near-real-time predictive waterfowl tracking system in two areas (Central Valley of California and Mid-Atlantic coast across Delaware, Maryland, Virginia, and North Carolina) with high waterfowl and commercial poultry populations (Figure 1). After validation, this approach could be further expanded to other poultry dense areas of the U.S. that spatially and temporally interface with waterfowl. Our goal is to leverage a series of well- demonstrated and cutting edge remote sensing technologies and research products including:NEXt generation RADar (NEXRAD) for waterfowl roosting location and densityHigh spatial resolution and temporal frequency waterfowl telemetry (i.e. location tracking) dataSatellite imagery and land-based sensing for tracking dynamic changes in surface water and land cover (i.e. waterfowl habitat) which are used to build predictive statistical models with respect to waterfowl location and density in near real-time in the Central Valley of California and the Mid-Atlantic coast andHigh-sensitivity ultra-filtration of wetland water and whole-segment M-RTPCR of AIV of wetland water, sediment and cloacal waterfowl samples . We will leverage NEXRAD, telemetry, and the geospatial habitat data to identify and target selected habitat (water and sediment) at high and low waterfowl densities in order to understand the viral ecology of AIV in wetlands in close proximity to commercial poultry.Specifically, we will collect cloacal swabs from waterfowl, wetland sediment and water for ultra-filtration (e.g. 10 gallons of wetland water will be filtered to less than 50 ml in order to concentrate virus). Subsequent M-segment RT-qPCR, whole-segment M-RTPCR and sequencing will be used to establish the relationship between waterfowl density and AIV viral prevalence in water, sediment and associated waterfowl. Our initial results which are in review by the Journal Transboundary & Emerging Diseases4 demonstrate that ultra-filtration in combination with the whole segment RT-PCR is superior to commonly used detection methods for AIV in water (i.e. no filtration with M-segment qPCR) which are well known to lack sensitivity and are not considered representative of AIV prevalence.5The above described data will be integrated into near-real-time predictive models which will be further validated and subsequently deployed as a web-app that poultry farmers, veterinarians, and regulators (USDA-APHIS and state departments of agriculture) can use as a risk-management tool to assess and manage risk related to AIV transmission to poultry from waterfowl.The combined analysis of waterfowl location, density, AIV presence and the molecular ecology of AIVs in waterfowl and the associated environment can better inform producers and other stakeholders enabling enhanced biosecurity practices (i.e. changes in husbandry practices, repairs to farm facilities and equipment, increased utilization of car-wash stations, foot baths, limiting sharing of equipment and workers between risky and non-risky farms). Similarly, the analysis of these data could significantly improve decision making (i.e. processing a flock early, placing of a flock later, and triaging veterinary visits) at an individual farm level during times of increased risk. To promote enhanced biosecurity decisions, from an extension perspective in year one we will use our university extension capabilities to develop a multi-disciplinary advisory team which will help guide web-app development with the goal of maximizing adoption of the web-app for various stakeholders. During years 2-4, the web-app will be beta tested and disseminated to stakeholders in a series of extension- based workshops across the Central Valley of California and the Mid-Atlantic Coast area by UC Davis and University of Delaware faculty and extension faculty. Additionally, surveys evaluating the web-app will be delivered to producers and other relevant stakeholders in years 2-4 electronically and via in-person extension based meetings in order to optimize the functionality/usability of the web-app.