Your browser doesn't support javascript.
loading
Adaptive sampling method to monitor low-risk pathways with limited surveillance resources.
Le, Thao P; Waring, Thomas K; Bondell, Howard; Robinson, Andrew P; Baker, Christopher M.
Afiliação
  • Le TP; The Centre of Excellence for Biosecurity Risk Analysis, The University of Melbourne, Parkville, Victoria, Australia.
  • Waring TK; Melbourne Centre for Data Science, The University of Melbourne, Parkville, Victoria, Australia.
  • Bondell H; School of Mathematics and Statistics, The University of Melbourne, Parkville, Victoria, Australia.
  • Robinson AP; The Centre of Excellence for Biosecurity Risk Analysis, The University of Melbourne, Parkville, Victoria, Australia.
  • Baker CM; Melbourne Centre for Data Science, The University of Melbourne, Parkville, Victoria, Australia.
Risk Anal ; 2024 Jun 11.
Article em En | MEDLINE | ID: mdl-38862404
ABSTRACT
The rise of globalization 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 increasingly lower risks require more samples. On a low-risk pathway that can be afforded only 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.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article