Delays in Global Disease Outbreak Responses: Lessons from H1N1, Ebola, and Zika
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In global disease outbreaks, there are significant time delays between the source of an outbreak and collective action. Some delay is necessary, but recent delays have been extended by insufficient surveillance capacity and time-consuming efforts to mobilize action. Three public health emergencies of international concern (PHEICs)-H1N1, Ebola, and Zika-allow us to identify and compare sources of delays and consider seven hypotheses about what influences the length of delays. These hypotheses can then motivate further research that empirically tests them. The three PHEICs suggest that deferred global mobilization is a greater source of delay than is poor surveillance capacity. These case study outbreaks support hypotheses that we see quicker responses for novel diseases when outbreaks do not coincide with holidays and when US citizens are infected. They do not support hypotheses that we see quicker responses for more severe outbreaks or those that threaten larger numbers of people. Better understanding the reason for delays can help target policy interventions and identify the kind of global institutional changes needed to reduce the spread and severity of future PHEICs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it