Evaluating the Timeliness of Enteric Disease Surveillance in British Columbia, Canada, 2012-13
Bibliographic record
Abstract
Timely surveillance of enteric diseases is necessary to identify and control cases and outbreaks. Our objective was to evaluate the timeliness of enteric disease surveillance in British Columbia, Canada, compare these results to other settings, and recommend improvements. In 2012 and 2013, information was collected from case report forms and laboratory information systems on 2615Salmonella, shigatoxin-producingE. coli,Shigella, andListeriainfections. Twelve date variables representing the surveillance process from onset of symptoms to case interview and final laboratory results were collected, and intervals were measured. The median time from onset of symptoms to reporting subtyping results to BC epidemiologists was 26–36 days and from onset of symptoms to case interview was 12–14 days. Our findings were comparable to the international literature except for a longer time (up to 29 day difference) to reporting of PFGE results to epidemiologists in BC. Such a delay may impact our ability to identify and solve outbreaks. Several process and system changes were implemented which should improve the timeliness of enteric disease surveillance.
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.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".