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Article . 2025 . Peer-reviewed
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Article . 2025
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Risk Analysis
Article . 2025
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Streamlining Pest Risk Assessment: The qPRAentry R Package for Assessing Potential Pest Entry

Authors: Rosace, Maria Chiara; Vicent, Antonio; Crotta, Matteo; Czwienczek, Ewelina; Makowski, David; Rossi, Vittorio; Cendoya, Martina;

Streamlining Pest Risk Assessment: The qPRAentry R Package for Assessing Potential Pest Entry

Abstract

ABSTRACT Pests' incursions pose a significant threat to agriculture and ecosystem integrity worldwide. Robust quantitative pest risk assessment (qPRA) methodologies are essential for effective evaluation of plant health risks posed by nonindigenous species. In this work, we introduce the comprehensive R package qPRAentry designed specifically for the initial phase of the qPRA, that is, the entry step, which evaluates the movement of a pest into a given area. The package encompasses functions for calculating the quantity of commodities imported from countries where a pest under assessment is present, and for implementing a pathway model able to assess the risk of potential entry of new pest founder populations. It can be easily implemented through the included functions or user‐friendly Shiny applications. An overview of qPRAentry's capabilities is presented, describing its functionalities, usage, and practical applications with two case studies that illustrate its performance, demonstrating the ability of the package to contribute to qPRA.

Country
France
Keywords

pathway models, [STAT.AP] Statistics [stat]/Applications [stat.AP], R package, pests' introduction, Animals, Pest Control, entry step, Risk Assessment, [SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy, Software, quantitative pest risk assessment

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid