Recurrent SARS-CoV-2 Infection: Case Reports and Review of the Literature
Bibliographic record
Abstract
We describe a 37-year-old woman who became infected with SARS-CoV-2. Over time, 4 other members in her family unit became infected, with 3/5 developing 2-3 separate clinical syndromes over two months. It is possible that each person had a single prolonged infection, with the literature reporting RNA detection for as long as 83 days in some cases. Syndromes of relapsing/remitting infection have also been well described. Intermittent negative RNA readings may represent “false negative” results with intermittent levels of viremia that occasionally fall below the limit of detection of the assay. An alternative explanation may be multiple episodes of infection, clearance, and re-infection within the family unit. Preliminary reports in the literature suggest onward transmission after recurrent infection in 3 reported cases. An understanding of the prevalence of cases series such as ours and their pathophysiologic and immunologic significance will improve our knowledge about SARS-CoV-2 infection and strategies to control it.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".