Identification of Underlying Factors Influencing the Immune Response to SARS-CoV-2 among workers and Residents in Long-term Care Homes: A Multi-province Study [C19-IS, study data contributed to the CITF Databank]
Bibliographic record
Abstract
Background: In many parts of Canada, an overwhelming number of COVID-19-related deaths occur in long-term care (LTC) homes. Investigations into the immunity and vaccine response in this population would help provide better protection in the future. Aims of the CITF co-funded study: The study aimed to determine risk factors that increase the probability of SARS-CoV-2 infection, re-infection, and hospitalization or death from COVID-19 in LTC homes. Methods: This prospective cohort study recruited LTC workers, caregivers, and residents, regardless of COVID-19 infection history, from Ontario and British Columbia LTC homes. All participants were over the age of 19 and completed a questionnaire at baseline and provided a dried blood spot sample for antibody identification at baseline and at up to five subsequent follow-ups. Contributed dataset contents:From 26 LTC homes in Ontario, the datasets include 2,459 participants (1,519 workers, 361 caregivers and 579 residents) who completed the baseline questionnaire between March 2021 and September 2022. 85% of participants gave one or more serology samples at baseline and during follow-up visits up to December 2022. A total of 4,947 samples were collected. From 12 LTC homes in British Columbia, the datasets include 651 participants (376 workers, 104 caregivers and 171 residents) who completed the baseline questionnaire between June 2021 and May 2023. 90% of participants gave one or more serology samples. A total of 1,555 samples were collected between Jan 2021 and May 2023. Variables include data in the following areas of information: demographics (year of birth, sex and gender, race-ethnicity, indigeneity, job role), general health (weight and height, smoking status, flu vaccination status, self-reported chronic conditions, self-rated health, access to health care), SARS-CoV-2 infection (positive test result, symptoms, hospitalizations), longitudinal follow-up for COVID vaccination, and serology and neutralization (IgA and IgG against SARS-CoV-2 receptor-binding domain (RBD), spike (S) protein, nucleocapsid (N) protein).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".