An outbreak of hepatitis A in Canada: The use of a control bank to conduct a case-control study
Bibliographic record
Abstract
An outbreak of 18 cases of hepatitis A virus infection across five Canadian provinces was investigated. Case onsets occurred between October 2017 and May 2018. A retrospective matched case-control study was conducted to identify the likely source of the outbreak. Three matched controls were recruited for each case using a previously established control bank, supplemented by landline and cell phone call lists. Univariate and multivariate matched analyses were conducted to identify a potential outbreak source. Seventy-two per cent of controls were recruited through the control bank, and required on average 25.5 calls per recruited control; 20% of controls were recruited through a landline sample and 8% of controls were recruited through a cell phone sample, requiring an average of 847.3 and 331.7 calls per recruited control, respectively. Results of the analysis pointed to shrimp/prawns (odds ratio (OR) 15.75, p = 0.01) and blackberries (OR 7.21, p = 0.02) as foods of interest, however, an outbreak source could not be confirmed. The control bank proved to be a more efficient method for control recruitment than random call lists. Expanding the control bank size and using alternative methods, such as online surveys, may prove beneficial for increasing the timeliness of a case-control study during an outbreak investigation.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".