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

Segaran P Pillai; Julia Fruetel; Todd West; Kevin Anderson; Patricia Hernandez; Cameron Ball; Carrie McNeil; Nataly Beck; Stephen A Morse

doi:10.3389/fbioe.2023.1234238

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

Front Bioeng Biotechnol. 2023 Sep 11:11:1234238. doi: 10.3389/fbioe.2023.1234238. eCollection 2023.

Authors

Segaran P Pillai^{1

2}, Julia Fruetel³, Todd West⁴, Kevin Anderson⁵, Patricia Hernandez³, Cameron Ball³, Carrie McNeil³, Nataly Beck³, Stephen A Morse⁶

Affiliations

¹ Office of the Commissioner, Food and Drug Administration, Silver Spring, MD, United States.
² U.S. Department of Health and Human Services, Washington, DC, United States.
³ Sandia National Laboratories, U.S. Department of Energy, Livermore, CA, United States.
⁴ Retired, Livermore, CA, United States.
⁵ Retired, Palmetto, FL, United States.
⁶ Retired, Atlanta, GA, United States.

Abstract

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.

Keywords: biennial review; decision support framework (DSF); multi-criteria decision analysis (MCDA); plant select agents; risk assessment tool.

Grants and funding

This work was funded by U.S. Department of Homeland Security, Science and Technology Directorate, Contract HSHQPM-15-X-00071. Author Segaran Pillai was employed by the Department of Homeland Security, Science and Technology Directorate and was actively involved in the study design, collection, analysis, interpretation of data, the writing of this article and the decision to submit it for publication.