Exercise Mataika: White Paper on response to a smallpox bioterrorism release in the Pacific
Bibliographic record
Abstract
Smallpox was declared eradicated in 1980, with known seed stock retained in two high security Biosafety Level 4 laboratories in the United States and Russia. Experts agree the likelihood of theft from these laboratories is low, and that synthetic creation of smallpox is a theoretical possibility. Until 2017 it was believed that synthetic smallpox was technically too complex a task to be a serious threat. However, in 2017, Canadian scientists synthesised a closely related orthopoxvirus, horsepox, using mail order DNA and $100,000. Simultaneously, terrorist groups have declared intent to conduct biological attacks. In this context an exercise was held on August 16th 2018, with international and cross-sectoral stakeholders to review preparedness for a bioterrorism attack in the Asia-Pacific region and globally. The exercise was conducted by The National Health and Medical Research Council (NHMRC) Centre for Research Excellence, Integrated Systems for Epidemic Response, with contextual input from the Ministry of Health and Medical Services Fiji. The scenario involved a deliberate release in Fiji, followed by a larger release in a more populous Asian country. Mathematical modelling was used to underpin epidemic projections under different conditions. The exercise alternated between clinical, public health, emergency and societal responses, with participants making real-time decisions on cross-sectoral response across the region and the world. Key weak points which are influential in determining the final size and impact of the epidemic were identified (based on mathematical modelling of transmission in Fiji and globally). We identified potential gaps in preparedness for smallpox and factors which influence the severity of a smallpox epidemic. This included identifying which determinants of epidemic size are potentially within our control, and which are not. Influential factors within our control include: preventing an attack through intelligence, law enforcement and legislation; speed of diagnosis; speed and completeness of case finding and case isolation; speed and security of vaccination response, including stockpiling; speed and completeness of contact tracing; protecting critical infrastructure and business continuity; non-pharmaceutical interventions (social distancing, PPE, border control); protecting first responders; operational support and logistics; social mobilisation and risk communication. Based on discussion at the workshop between diverse stakeholders, recommendations were made to guide improved prevention, mitigation and rapid response, thus providing a holistic, cross-sectoral framework for prevention of a worst-case scenario smallpox pandemic.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".