Annually, more than one billion people travel around the world and about one fourth of the total agricultural commodities are imported. Food products enter the US from over 250,000 foreign establishments from 180 countries. Approximately, 50 percent of U.S. agricultural imports are horticultural products: fruits, vegetables, tree nuts, nursery stock, cut flowers, and hops. As the number of travelers and the volume of commodities imported annually increases by 4%; the risk of accidental or intentional introduction of pests and disease threats (PDTs) is significant. More than 1500 cross-border PDTs could disrupt the health, security and trade of the US. Therefore, a strong domestic agricultural disease and pest detection system is an essential capability to provide a continuum of offshore preclearance and efficient domestic port inspections of passenger luggage, cargo and shipments.
Modeling approaches to prioritize inspections using historical data for ornamental imports have used multinomial logistic (MNL) regression, genetic algorithm for rule-set prediction (GARP), time series modeling. This approach has a well-established theoretical grounding in statistics and dynamic systems theory. A key aspect of this approach is that training data can be sampled from the same distribution. This project seeks to address the U.S. need to prevent the accidental and intentional introduction of PDTs. In the next twelve months, we will develop predictive, forecasting techniques to identify and flag high-risk passenger baggage, cargo and mail shipments. To achieve our goal, we will implement Pest and Disease Forecasting System. This multilayered biodefense analytical enterprise is cohesive well-curated data source coupled with time series statistical forecasting. In parallel, we will advance the development of an artificial intelligence. Main Mission: Develop state-of-the-art decentralized forecasting and analytical system that mitigates the risk posed diseases and pests threats to border security, health and trade. (Milestone 1) Develop an Optimal Model for DPTs Pathway Trends and Risk from Baggage and Cargo. (Milestone 2) Develop PDT Risk-Based Analysis System for Baggage and Cargo Prioritization.