Clinical Risk, Sociodemographic Factors, and SARS-CoV-2 Infection Over Time in Ontario, Canada
Bibliographic record
Abstract
Abstract Background Sociodemographic and clinical factors are emerging as important predictors for developing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Objective To determine whether public health interventions that culminated in a stay-at-home lockdown instituted during the first wave of the pandemic in March/April 2020 were effective at mitigating the association of any of these factors with the risk of infection. Design Population-based cohort study Setting Ontario, Canada Patients All adults that underwent testing for SARS-CoV-2 between January 1 and June 12, 2020. Measurements The outcome of interest was SARS-CoV-2 infection, determined by reverse transcription polymerase chain reaction testing. Adjusted odds ratios (ORs) were determined for sociodemographic and clinical risk factors before and after the peak of the pandemic to assess for changes in effect sizes. Results Among 578,263 community-dwelling individuals, 20,524 (3.5%) people tested positive. The association between age and SARS-CoV-2 infection risk among tested community-dwelling individuals varied over time (P-interaction <0.0001). Prior to the first-wave peak of the pandemic, the likelihood of SARS-CoV-2 infection increased progressively with age compared with individuals aged 18-45 years (P<0.0001). This association subsequently reversed, with all age groups younger than 85 years at progressively higher risk of infection (P<0.0001) after the peak. Otherwise, risk factors that persisted throughout included male sex, residing in lower income neighborhoods, residing in more racially/ethnically diverse communities, immigration to Canada, and history of hypertension and diabetes. While there was a reduction in infection rates across Ontario after mid-April, there was less impact in regions with higher degrees of racial/ethnic diversity. When considered in an additive risk model, following the initial peak of the pandemic, individuals living in the most racially/ethnically diverse communities with 2, 3, or ≥4 risk factors had ORs of 1.89, 3.07, and 4.73-fold higher for SARS-CoV-2 infection compared to lower risk individuals in their community (all P<0.0001). In contrast, in the least racially/ethnically diverse communities, there was little to no gradient in infection rates across risk strata. Conclusion After public health interventions in March/April 2020, people with multiple risk factors residing in the most racially diverse communities of Ontario continued to have the highest likelihood of SARS-CoV-2 infection while risk was mitigated for people with multiple risk factors residing in less racially/ethnically diverse communities. Further efforts are necessary to reduce the risk of SARS-CoV-2 infection among the highest risk individuals residing in these communities. Primary Funding Source Canadian Institutes of Health Research and the Ted Rogers Centre for Heart Research.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".