Protection conferred by SARS-CoV-2 infection across a spectrum of reinfection symptoms and severities
Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 infection is associated with protection against reinfection. This study analysed this protection across different reinfection symptoms and severities, comparing the preomicron and omicron eras. METHODS: A nationwide, matched, test-negative, case-control study was conducted in Qatar from 5 February 2020 to 12 March 2024. The preomicron analysis used a sample of 509 949 positive and 8 494 782 negative tests, while the omicron analysis included 682 257 positive and 6 904 044 negative tests. Data were sourced from Qatar's national databases for COVID-19 laboratory testing, vaccination, hospitalisation and death. RESULTS: Effectiveness of preomicron infection against preomicron reinfection was estimated at 80.9% (95% CI: 79.1% to 82.6%) for asymptomatic reinfection, 87.5% (95% CI: 86.1% to 88.9%) for symptomatic reinfection, 97.8% (95% CI: 95.7% to 98.9%) for severe COVID-19 reinfection, 100.0% (95% CI: 97.5% to 100.0%) for critical COVID-19 reinfection and 88.1% (95% CI: 50.3% to 97.2%) for fatal COVID-19 reinfection. For omicron infection against omicron reinfection, the estimates were 46.4% (95% CI: 36.9% to 54.4%) for asymptomatic reinfection, 52.8% (95% CI: 44.4% to 60.0%) for symptomatic reinfection, 100.0% (95% CI: 55.4% to 100.0%) for severe COVID-19 reinfection, 100.0% (95% CI: 15.1% to 100.0%) for critical COVID-19 reinfection, and 75.2% (95% CI: -58.8% to 97.5%) for fatal COVID-19 reinfection. Effectiveness over time since previous infection showed no discernible decline in protection against all forms of reinfection in the preomicron era, but a rapid decline against asymptomatic and symptomatic reinfections in the omicron era. CONCLUSIONS: A gradient of protection against reinfection is evident, with the highest protection observed against severe forms of COVID-19. Over time, this gradient becomes more pronounced, as protection against asymptomatic and symptomatic reinfections decreases, while protection against severe outcomes remains strong.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".