Beyond the Dirty Dozen: A Proposed Methodology for Assessing Future Bioweapon Threats
Bibliographic record
Abstract
Background: Defense policy planners and countermeasure developers are often faced with vexing problems involving the prioritization of resources and efforts. This is especially true in the area of Biodefense, where each new emerging infectious disease outbreak brings with it questions regarding the causative agent's potential for weaponization. Recent experience with West Nile Virus, Severe Acute Respiratory Syndrome, Monkeypox, and H1N1 Influenza highlights this problem. Appropriately, in each of these cases, the possibility of bioterrorism was raised, although each outbreak ultimately proved to have a natural origin. In fact, determining whether an outbreak has an unnatural origin can be quite difficult. Thus, the questions remain: could the causative agents of these and other emerging infectious disease outbreaks pose a future weaponization threat? And how great is that threat? Should precious resources be diverted from other defense efforts in order to prepare for possible hostile employment of novel diseases by belligerents? Answering such critical questions requires some form of systematic threat assessment. Methods: Through extensive collaborative work conducted within NATO's Biomedical Advisory Council, we developed a scoring matrix for evaluating the weaponization potential of the causative agents of such diseases and attempted to validate our matrix by examining the reproducibility of data using known threat agents. Our matrix included 12 attributes of a potential weapon and was provided, along with detailed scoring instructions, to 12 groups of biodefense experts in 6 NATO nations. Study participants were asked to score each of these 12 attributes on a scale of 0-3: Infectivity, Infection-to-Disease Ratio (Reliability), Predictability (& Incubation Period), Morbidity & Mortality (Virulence), Ease of Large-Scale Production & Storage, Aerosol Stability, Atmospheric Stability, Ease of Dispersal, Communicability, Prophylactic Countermeasure Availability, Therapeutic Countermeasure Availability, and Ease of Detection. Reproducibility of scoring data was assessed by examining the standard deviations (SD) of mean scores. Results: Our results were unexpected. Several familiar biothreat diseases such as anthrax and tularemia were judged, by our experts, to be less threatening than many others owing to a number of factors including ease of detection, lack of communicability, and the ready availability of countermeasures. Conversely, several toxins were judged by experts to have very high potential as threat agents owing, in part, to their reliability, virulence, and a lack of available countermeasures. Agreement among experts, as determined by lower SD about a mean score, was greater for more familiar threats. Discussion: Our study was designed to provide a concise and east-to-apply set of criteria that could be used by NATO nations to evaluate emerging infectious disease threats with respect to their weaponization potential. Our results were unexpected. We believe that a lack of appropriate weighting factors may explain these results and suggest that future studies weigh each of the 12 proposed criteria based on the intended use of the assessment data and other situational factors. We believe that the greatest value of our study lies in a codification of the attributes of a biological weapon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.031 | 0.092 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.017 | 0.011 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".