A systematic review of the impact of the Alpha and Gamma variants of concern on hospitalization and symptomatic rates of SARS-CoV-2
Bibliographic record
Abstract
Abstract The hospitalization and symptomatic rates of Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (SARS-CoV-2) are key epidemiological parameters affecting risk analyses conducted for the Canadian Armed Forces (CAF) during the Coronavirus Disease-19 (COVID-19) pandemic. As one of the criteria of a variant of concern (VOC) is that it affects disease severity, the authors sought to understand whether the Alpha and Gamma VOCs are significantly different in these two parameters than the original wildtype of SARS-CoV-2, the most prevalent in relevant areas of Canada as of study initiation. Searches for studies were conducted in Scopus and PubMed, and located through following citations and receiving studies from daily literature scans. For the hospitalization outcome, effect ratios relative to original wildtype were included. For the symptomatic ratio, the ratio itself for each variant was used. Analysis of age-related effects was of particular value, as CAF members are primarily adults under the age of 60. The firmest conclusion of this review is that the Alpha VOC comes with a higher relative risk of hospitalization compared to the original wildtype, most likely above 1.4, while unlikely to be above 2, with the balance of evidence being that the relative risk is not significantly modified by age. The evidence for Gamma is more limited, but the odds ratio may be above 2, and potentially much greater than that, especially for those 20-39 years of age. For both VOCs reports on symptomatic ratio differed on whether there was an effect, as well as its potential direction.
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 | 0.009 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".