SARS-CoV-2 infection among healthcare workers: the role of occupational and household exposures during the first three pandemic waves in Quebec, Canada
Bibliographic record
Abstract
Objective: We described the evolution of SARS-CoV-2 source of infection in a cohort of healthcare workers (HCWs) of Quebec, Canada, during the first three pandemic waves. We also estimated their household secondary attack rate (SAR) and its risk factors. Design: Cross-sectional surveys. Participants: HCWs with a SARS-CoV-2 infection confirmed by polymerasa chain reaction and diagnosed between March 2020 and May 2021. Methods: We collected demographic, clinical, vaccination, and employment information, self-reported perceived source of infection, and transmission to household members during the first three pandemic waves. SAR was calculated for households with ≥2 members where the HCW was the index case. A Poisson regression model estimated the association between risk factors and SAR. Results: Among the 11,670 HCWs completing the survey, 91%, perceived their workplace as the source of infection during the first wave (March-July 2020), 71% during the second wave (July 2020-March 2021), and 40% during the third wave (March-May 2021). Conversely, HCWs reported an increasing proportion of household-acquired infections with each wave from 4% to 14% and 33%, respectively. The overall household SAR of 7,990 HCWs living with ≥1 person was 30% (95%CI: 29-30). SAR increased with the presence of symptoms, older age, and during Alpha-variant predominant period. Conclusions: HCWs and their household members were largely affected during the first pandemic waves of COVID-19, but the relative importance of occupational exposure changed overtime. Pandemic preparedness in healthcare settings is essential to protect HCWs from emerging biological hazard exposures.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".