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Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making

The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident respo...

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Autores principales: Pillai, Segaran P., Fruetel, Julia, West, Todd, Anderson, Kevin, Hernandez, Patricia, Ball, Cameron, McNeil, Carrie, Beck, Nataly, Morse, Stephen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520701/
https://www.ncbi.nlm.nih.gov/pubmed/37767109
http://dx.doi.org/10.3389/fbioe.2023.1234238
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author Pillai, Segaran P.
Fruetel, Julia
West, Todd
Anderson, Kevin
Hernandez, Patricia
Ball, Cameron
McNeil, Carrie
Beck, Nataly
Morse, Stephen A.
author_facet Pillai, Segaran P.
Fruetel, Julia
West, Todd
Anderson, Kevin
Hernandez, Patricia
Ball, Cameron
McNeil, Carrie
Beck, Nataly
Morse, Stephen A.
author_sort Pillai, Segaran P.
collection PubMed
description The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident response, and the security of entities working with them. Every 2 years the USDA DASAT reviews their select agent list, utilizing assessments by subject matter experts (SMEs) to rank the agents. We explored the applicability of multi-criteria decision analysis (MCDA) techniques and a decision support framework (DSF) to support the USDA DASAT biennial review process. The evaluation includes both current and non-select agents to provide a robust assessment. We initially conducted a literature review of 16 pathogens against 9 criteria for assessing plant health and bioterrorism risk and documented the findings to support this analysis. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for ensuring accuracy. Scoring criteria were adopted to ensure consistency. The MCDA supported the expectation that select agents would rank high on the relative risk scale when considering the agricultural consequences of a bioterrorism attack; however, application of analytical thresholds as a basis for designating select agents led to some exceptions to current designations. A second analytical approach used agent-specific data to designate key criteria in a DSF logic tree format to identify pathogens of low concern that can be ruled out for further consideration as select agents. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making.
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spelling pubmed-105207012023-09-27 Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making Pillai, Segaran P. Fruetel, Julia West, Todd Anderson, Kevin Hernandez, Patricia Ball, Cameron McNeil, Carrie Beck, Nataly Morse, Stephen A. Front Bioeng Biotechnol Bioengineering and Biotechnology The United States Department of Agriculture (USDA) Division of Agricultural Select Agents and Toxins (DASAT) established a list of biological agents (Select Agents List) that threaten crops of economic importance to the United States and regulates the procedures governing containment, incident response, and the security of entities working with them. Every 2 years the USDA DASAT reviews their select agent list, utilizing assessments by subject matter experts (SMEs) to rank the agents. We explored the applicability of multi-criteria decision analysis (MCDA) techniques and a decision support framework (DSF) to support the USDA DASAT biennial review process. The evaluation includes both current and non-select agents to provide a robust assessment. We initially conducted a literature review of 16 pathogens against 9 criteria for assessing plant health and bioterrorism risk and documented the findings to support this analysis. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for ensuring accuracy. Scoring criteria were adopted to ensure consistency. The MCDA supported the expectation that select agents would rank high on the relative risk scale when considering the agricultural consequences of a bioterrorism attack; however, application of analytical thresholds as a basis for designating select agents led to some exceptions to current designations. A second analytical approach used agent-specific data to designate key criteria in a DSF logic tree format to identify pathogens of low concern that can be ruled out for further consideration as select agents. Both the MCDA and DSF approaches arrived at similar conclusions, suggesting the value of employing the two analytical approaches to add robustness for decision making. Frontiers Media S.A. 2023-09-11 /pmc/articles/PMC10520701/ /pubmed/37767109 http://dx.doi.org/10.3389/fbioe.2023.1234238 Text en Copyright © 2023 Pillai, Fruetel, West, Anderson, Hernandez, Ball, McNeil, Beck and Morse. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Pillai, Segaran P.
Fruetel, Julia
West, Todd
Anderson, Kevin
Hernandez, Patricia
Ball, Cameron
McNeil, Carrie
Beck, Nataly
Morse, Stephen A.
Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title_full Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title_fullStr Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title_full_unstemmed Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title_short Application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
title_sort application of multi-criteria decision analysis techniques and decision support framework for informing plant select agent designation and decision making
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10520701/
https://www.ncbi.nlm.nih.gov/pubmed/37767109
http://dx.doi.org/10.3389/fbioe.2023.1234238
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