SARS-CoV-2 seroprevalence among Vancouver public school staff in British Columbia, Canada
Bibliographic record
Abstract
Abstract Importance Contact-tracing studies suggest minimal secondary transmission in schools. However, there are limited school data accounting for asymptomatic cases, particularly late in the 2020/21 school year, and in the context of uninterrupted in-person schooling and widespread community transmission. Objectives To determine the SARS-CoV-2 seroprevalence in a sample of school staff, compared to the community, and to COVID-19 rates among all students and staff within the same school population. Design Incident COVID-19 cases among students and school staff using public health data, with an embedded cross-sectional serosurvey among school staff sampled from February 10 to May 15, 2021, comparing to age, sex and geographic location-matched blood donors sampled in January 2021. Setting Vancouver School District (British Columbia, Canada) from kindergarten to grade 12. Participants Active s chool staff enrolled from February 3 to April 23, 2021. Main outcome measures SARS-CoV-2 antibodies in a sample of school staff using spike (S)-based testing (unvaccinated staff) or N-based serology testing (vaccinated staff). Results The incidence of COVID-19 cases among students attending in-person was 9.8 per 1,000 students during the 2020/21 school year (N = 47,280 students), and among staff was 13 per 1,000 since the beginning of the pandemic (N = 7,071 active school staff). In total, 1,689 school staff (64% elementary, 28% secondary, 8.3% school board staff or multiple grades) completed the questionnaire, 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% (363/1,686) reported close contact with a COVID-19 case, only 1.4% (24/1688) of the school staff reported having had a positive viral nucleic acid test. Of this group, five believed they acquired the infection at school. The adjusted seroprevalence in staff who gave blood (1,556/1,689, 92.1%) was 2.3% [95%CI: 1.6 – 3.2%] compared to 2.3% [95%CI: 1.7 – 3.0%] in blood donors. Conclusion and relevance Despite high reported COVID-19 cases among students and staff, and frequent within-school exposures, we found no detectable increase in seroprevalence among school staff above the community seroprevalence. These findings corroborate claims that, with appropriate mitigation strategies, in-person schooling is not associated with significantly increased risk for school staff. Key Points Question What was the prevalence of COVID-19 infections in school staff who maintained in-person schooling during the 2020/21 school year in Vancouver, British Columbia, and how does it compare to the risk of COVID-19 infection in the community. Findings As of March 4, 2021, the incidence of COVID-19 cases among school staff was 13 per 1,000 (N = 7,071 school staff) since the beginning of the pandemic. In a cross-sectional seroprevalence analysis from February 10 to May 15, 2021, the adjusted seroprevalence among a sample of school staff (N = 1,556) was 2.3% [95%CI: 1.6 – 3.2%], compared to 2.3% [95%CI: 1.7 – 3.0%] in 1:2 age, sex and geographical location (by postal code)-matched reference group of blood donors. Meaning We found no detectable increase in seroprevalence among school staff above the community seroprevalence. These findings corroborate claims that, with appropriate mitigation strategies in place, in-person schooling is not associated with significantly higher risk for school staff.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".