Adaptive sampling method to monitor low-risk pathways with limited surveillance resources

TL;DR

This paper introduces an adaptive sampling method that efficiently monitors low-risk trade pathways by focusing on risk thresholds rather than precise risk estimation, optimizing limited inspection resources.

Contribution

The paper proposes a novel threshold-based adaptive sampling approach that reduces sampling needs while effectively monitoring low-risk pathways.

Findings

Requires less sampling than previous methods

Effectively detects significant risk changes

Supports efficient resource allocation

Abstract

The rise of globalisation has led to a sharp increase in international trade, with high volumes of containers, goods and items moving across the world. Unfortunately, these trade pathways also facilitate the movement of unwanted pests, weeds, diseases, and pathogens. Each item could contain biosecurity risk material, but it is impractical to inspect every item. Instead, inspection efforts typically focus on high risk items. However, low risk does not imply no risk. It is crucial to monitor the low risk pathways to ensure that they are and remain low risk. To do so, many approaches would seek to estimate the risk to some precision, but the lower the risk, the more samples needed to estimate the risk. On a low-risk pathway that can be afforded more limited inspection resources, it makes more sense to assign fewer samples to the lower risk activities. We approach the problem by introducing two thresholds. Our method focuses on letting us know whether the risk is below certain thresholds, rather than estimating the risk precisely. This method also allows us to detect a significant change in risk. Our approach typically requires less sampling than previous methods, while still providing evidence to regulators to help them efficiently and effectively allocate inspection effort.