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. (Frontiers in Bioengineering and Biotechnology, 2023)
The United States Department of Agriculture (USDA) Select Agent Program (SAP) establishes 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 two years the USDA SAP 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 SAP 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 should 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.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. All authors declare no other competing interest.