Contaminated consignment simulation to support risk‐based inspection design

Abstract

Invasive nonnative plant pests can cause extensive environmental and economic damage and are very difficult to eradicate once established. Phytosanitary inspections that aim to prevent biological invasions by limiting movement of nonnative plant pests across borders are a critical component of the biosecurity continuum. Inspections can also provide valuable information about when and where plant pests are crossing national boundaries. However, only a limited portion of the massive volume of goods imported daily can be inspected, necessitating a highly targeted, riskbased strategy. Furthermore, since inspections must prioritize detection and efficiency, their outcomes generally cannot be used to make inferences about risk for cargo pathways as a whole. Phytosanitary agencies need better tools for quantifying pests going undetected and designing risk-based inspection strategies appropriate for changing operational conditions. In this research, we present PoPS (Pest or Pathogen Spread) Border, an open-source consignment inspection simulator for measuring inspection outcomes under various cargo contamination scenarios to support recommendations for inspection protocols and estimate pest slippage rates. We used the tool to estimate contamination rates of historical interception data, quantify tradeoffs in effectiveness and workload for inspection strategies, and identify vulnerabilities in sampling protocols as changes in cargo configurations and contamination occur. These use cases demonstrate how this simulation approach permits testing inspection strategies and measuring quantities that would otherwise be impossible in a field-based setting. This work represents the first steps toward a decision support tool for creating dynamic inspection protocols that respond to changes in available resources, workload, and commerce trends.

Efficient border biosecurity inspection leverages superspreading to reduce biological invasion risk

“…We showed that overdispersion (i.e., the fact that consignments in the same pathway have different infestation rates) is a common feature of border biosecurity data. The few other studies that looked into this issue also found evidence of overdispersion in Japan, the United States, and Australia (Clark et al, 2023;Montgomery et al, 2022;Yamamura & Sugimoto, 1995). We then derived a propagule pressure equation for overdispersed pathways and used it to formulate an optimal sample size under budget constraints.…”

“…While we could simulate the filtering effect of inspections on the different consignments that arrive at the border using Monte Carlo methods (Montgomery et al., 2022), the Bayesian framework provides a more tractable approach to this problem. In this section, we assume that pathways are overdispersed and that the distribution of infestation rate among different consignments of a pathway can be modeled by a beta distribution.…”

Forecasting global spread of invasive pests and pathogens through international trade

“…It has been used in collaboration with government and other partners to forecast the spread of Phytophthora ramorum , the causal agent of sudden oak death, and spotted lanternfly (Gaydos et al, 2021; Jones et al, 2021). Together with PoPS Border, a consignment inspection simulator used for designing dynamic, risk‐based sampling protocols at national ports of entry (Montgomery et al, 2023), these three models form a suite of tools developed to support phytosanitary management decisions along the biosecurity continuum.…”