Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making
The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2022.756586/full |
| _version_ | 1818232397221593088 |
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| author | Segaran P. Pillai Julia A. Fruetel Kevin Anderson Rebecca Levinson Patricia Hernandez Brandon Heimer Stephen A. Morse |
| author_facet | Segaran P. Pillai Julia A. Fruetel Kevin Anderson Rebecca Levinson Patricia Hernandez Brandon Heimer Stephen A. Morse |
| author_sort | Segaran P. Pillai |
| collection | DOAJ |
| description | The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions. |
| first_indexed | 2024-12-12T11:05:38Z |
| format | Article |
| id | doaj.art-3d30f87ee312487b995462d32583be51 |
| institution | Directory Open Access Journal |
| issn | 2296-4185 |
| language | English |
| last_indexed | 2024-12-12T11:05:38Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj.art-3d30f87ee312487b995462d32583be512022-12-22T00:26:25ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852022-06-011010.3389/fbioe.2022.756586756586Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision MakingSegaran P. Pillai0Julia A. Fruetel1Kevin Anderson2Rebecca Levinson3Patricia Hernandez4Brandon Heimer5Stephen A. Morse6Office of the Commissioner, Food and Drug Administration, U.S. Department of Health and Human Services, Silver Spring, MD, United StatesSandia National Laboratory, U.S. Department of Energy, Livermore, CA, United StatesScience and Technology Directorate, U.S. Department of Homeland Security, Washington, DC, United StatesSandia National Laboratory, U.S. Department of Energy, Livermore, CA, United StatesSandia National Laboratory, U.S. Department of Energy, Livermore, CA, United StatesSandia National Laboratory, U.S. Department of Energy, Livermore, CA, United StatesIHRC, Inc., Atlanta, GA, United StatesThe Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.https://www.frontiersin.org/articles/10.3389/fbioe.2022.756586/fullselect agents and toxinsrisk assesmentmulti-criterialogic tree analysisbiosecurity |
| spellingShingle | Segaran P. Pillai Julia A. Fruetel Kevin Anderson Rebecca Levinson Patricia Hernandez Brandon Heimer Stephen A. Morse Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making Frontiers in Bioengineering and Biotechnology select agents and toxins risk assesment multi-criteria logic tree analysis biosecurity |
| title | Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making |
| title_full | Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making |
| title_fullStr | Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making |
| title_full_unstemmed | Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making |
| title_short | Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making |
| title_sort | application of multi criteria decision analysis techniques for informing select agent designation and decision making |
| topic | select agents and toxins risk assesment multi-criteria logic tree analysis biosecurity |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2022.756586/full |
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