Age-Specific Changes in Virulence Associated with SARS-CoV-2 Variants of Concern
Bibliographic record
Abstract
Abstract Background Novel variants of concern (VOCs) have been associated with both increased infectivity and virulence of SARS-CoV-2. The virulence of SARS-CoV-2 is closely linked to age. Whether relative increases in virulence of novel VOCs is similar across the age spectrum, or is limited to some age groups, is unknown. Methods We created a retrospective cohort of people in Ontario, Canada testing positive for SARS-CoV-2 and screened for VOCs, with dates of test report between February 7 and August 30, 2021 (n=233,799). Cases were classified as N501Y-positive VOC, probable Delta VOC, or VOC undetected. We constructed age-specific logistic regression models to evaluate the effects of N501Y-postive or Delta VOC infections on infection severity, using hospitalization, intensive care unit (ICU) admission, and death as outcome variables. Models were adjusted for sex, time, health unit, vaccination status, comorbidities, immune compromise, long-term care residence, healthcare worker status, and pregnancy. Results Infection with either N501Y-positive or Delta VOCs was associated with significant elevations in risk of hospitalization, ICU admission, and death in younger and older adults, compared to infections where a VOC was not detected. Delta VOC increased hospitalization risk in children under 10 by a factor of 2.5 (adjusted odds ratio, 95% confidence interval: 1.2 to 5.1) compared to non-VOC. For most VOC-outcome combinations there was no heterogeneity in adverse outcomes by age. However, there was an inverse relationship between age and relative increase in risk of death with delta VOC, with younger age groups showing a greater relative increase in risk of death than older individuals. Interpretation SARS-CoV-2 VOCs appear to be associated with increased relative virulence of infection in all age groups, though low absolute numbers of outcomes in younger individuals make estimates in these groups imprecise.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".