Challenges in Listeriosis Cluster and Outbreak Investigations, Province of Quebec, 1997–2011
Bibliographic record
Abstract
OBJECTIVES: Public health authorities place a high priority on investigating listeriosis outbreaks, and these epidemiological investigations remain challenging. Some approaches have been described in the literature to address these challenges. This review of listeriosis clusters and outbreaks investigated in the Province of Quebec (Quebec) highlights investigative approaches that contributed to identifying the source of these outbreaks. MATERIALS: The Laboratoire de Santé Publique du Québec (LSPQ) implemented pulsed-field gel electrophoresis (PFGE) molecular subtyping in 1997 to identify Listeria monocytogenes clusters among isolates from invasive listeriosis cases identified throughout Quebec. A cluster was defined as three cases or more with the same or similar PFGE profiles (≤3 band difference) occurring over a 4-month period. An investigation was initiated if the epidemiologic indicators suggested a common source. Listeriosis data from LSPQ's database were reviewed to identify and describe clusters detected from 1997 to 2011, including those that led to an outbreak investigation. Epidemiological reports prepared following each outbreak were also reviewed. RESULTS: Eleven clusters were identified in the province by LSPQ between 1997 and 2011. Outbreak investigations were initiated for six clusters, four of which involved more than 10 cases. Factors that contributed to identifying the source for three of these outbreaks highlighted the value of (1) making all stakeholders (food safety and inspection services, public health authorities, and laboratories) aware of any ongoing investigation and sharing relevant information even if the source is not yet identified; (2) promptly collecting food samples identified and considered as possible vehicles of infection identified during the interview of a Listeria case; (3) collecting food items and/or environmental samples in locations reported in common by cases in the same cluster. CONCLUSIONS: Multiple approaches should be considered when investigating L. monocytogenes clusters. Networks to facilitate continuous exchange of human and food data between public health and food safety partners should be encouraged.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".