SARS-CoV-2 seroprevalence among Vancouver public school staff in British Columbia, Canada: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: Few studies reported COVID-19 cases in schools during the 2020/21 academic year in a setting of uninterrupted in-person schooling. The main objective was to determine the SARS-CoV-2 seroprevalence among school staff in Vancouver public schools. DESIGN: Cumulative incident COVID-19 cases among all students and school staff based on public health data, with an embedded cross-sectional serosurvey among a school staff sample that was compared to period, age, sex and geographical location-weighted data from blood donors. SETTING: Vancouver School District (British Columbia, Canada) from kindergarten to grade 12. PARTICIPANTS: Active school staff enrolled from 3 February to 23 April 2021 with serology testing from 10 February to 15 May 2021. MAIN OUTCOME MEASURES: SARS-CoV-2 seroprevalence among school staff, based on spike (S)-based (unvaccinated staff) or N-based serology testing (vaccinated staff). RESULTS: Public health data showed the cumulative incidence of COVID-19 among students attending in-person was 9.8 per 1000 students (n=47 280), and 13 per 1000 among school staff (n=7071). In a representative sample of 1689 school staff, 78.2% had classroom responsibilities, and spent a median of 17.6 hours in class per week (IQR: 5.0-25 hours). Although 21.5% (363/1686) of surveyed staff self-reported close contact with a COVID-19 case outside of their household (16.5% contacts were school-based), 5 cases likely acquired the infection at school based on viral testing. Sensitivity/Specificity-adjusted seroprevalence in 1556/1689 staff (92.1%) was 2.3% (95% CI: 1.6% to 3.2%), comparable to a sex, age, date and residency area-weighted seroprevalence of 2.6% (95% CI: 2.2% to 3.1%) among 5417 blood donors. CONCLUSION: Seroprevalence among staff was comparable to a reference group of blood donors from the same community. These data show that in-person schooling could be safely maintained during the 2020/21 school year with mitigation measures, in a large school district in Vancouver, Canada.
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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 | 0.004 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".