P-88 Risk of SARS-CoV-2 infection in a large cohort of Ontario workers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<h3>Introduction</h3> Work is a key determinant of COVID-19 outcomes, however occupational surveillance is a critical information gap in many countries, including Canada. Understanding the risk of SARS-CoV-2 by occupation can identify high risk groups that can be targeted for prevention strategies. <h3>Materials and Methods</h3> The cohort includes 1,205,847 former workers compensation (non-COVID-19) claimants (aged 15–65) linked to health databases in Ontario, Canada. Incident cases were defined as either having a confirmed positive polymerase chain reaction (PCR) test in the Ontario Laboratory Information System (OLIS), or an International Classification of Diseases (ICD-10-CA) diagnostic code of U07.1 in hospitalization or emergency department records (February 2020-December 2021). Workers were followed until diagnosis, death, emigration, age 65 or end of follow-up. Sex- and age-adjusted Cox proportional hazards models were used to estimate hazards ratios (HR) and 95% confidence intervals (CI) by occupation, compared to all other cohort members. Analyses were also conducted to examine occupational trends in testing and diagnosis during waves of infection. <h3>Results</h3> Overall, 80,740 COVID-19 cases were diagnosed among workers during follow-up, of those, 80% were diagnosed with a positive PCR test. Associations were identified between COVID-19 diagnosis and employment in nursing (HR=1.44, CI95%=1.40–1.49), air transport operating (HR=1.61, CI95%=1.47–1.77), textile/fur/leather products fabricating, assembling, and repairing (HR=1.38, CI95%=1.25–1.54), apparel and furnishing services (HR=1.38, CI95%=1.19–1.60), and janitor and cleaning services (HR=1.11, CI95%=1.06–1.16). Restricted analyses where health care workers were omitted from the comparison group strengthened some associations for other high-risk workers. Test positivity ranged between 4–16% across major occupation groups. Risks varied over time and with changes in protective measures in workplaces and in broader communities. <h3>Conclusions</h3> Elevated risk of SARS-CoV-2 infection in health care, manufacturing, transportation, and service workers were identified, underscoring the importance of including occupational data in COVID-19 surveillance. Occupational trends in severe outcomes and vaccination are also being explored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it