Protection of natural infection against reinfection with SARS-CoV-2 JN.1 variant
Bibliographic record
Abstract
Abstract This study investigated the effectiveness of natural infection in preventing reinfection with the JN.1 variant during a large JN.1 wave in Qatar, using a test-negative case-control study design. The overall effectiveness of previous infection in preventing reinfection with JN.1 was estimated at only 1.8% (95% CI: −9.3-12.6%). This effectiveness demonstrated a rapid decline over time since the previous infection, decreasing from 82.4% (95% CI: 40.9-94.7%) within 3 to less than 6 months after the previous infection to 50.9% (95% CI: −11.8-78.7%) in the subsequent 3 months, and further dropping to 18.3% (95% CI: −34.6-56.3%) in the subsequent 3 months. Ultimately, it reached a negligible level after one year. The findings show that the protection of natural infection against reinfection with JN.1 is strong only among those who were infected within the last 6 months, with variants such as XBB*. However, this protection wanes rapidly and is entirely lost one year after the previous infection. The findings support considerable immune evasion by JN.1.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".