Nontraditional infectious diseases surveillance systems
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
This chapter describes nontraditional infectious diseases surveillance systems, which complement the formal public health system. One such nontraditional system, ProMED-mail, is a rapid reporting system of emerging infectious diseases in humans, animals, and plants. ProMED-mail focuses on rapid reporting and relies on local sources like newspapers and their websites and local rapporteurs submitting reports of unusual events. GeoSentinel data have been used to determine the seasonality of dengue by region of travel and risk of acquiring schistosomiasis by destination, and to identify unusual outbreaks such as sarcocystosis on Tioman Island, Malaysia. Numerous other programs have begun to use informal-source surveillance, including automated systems like HealthMap and Canada's Global Public Health Information Network (GPHIN), Medisys and others as well as more human-driven systems such as FluTrackers. Recent work has demonstrated that the time from the beginning of an outbreak until its detection and public reporting has been reduced as informal-source surveillance has blossomed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it