Children with SARS-CoV-2 infection during an epidemic in China (outside of Hubei province)
Bibliographic record
Abstract
BACKGROUND: Limited studies have reported the clinical and epidemiological characteristics of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to provide the epidemiological characteristics of children with COVID-19 throughout China (outside of Hubei Province) based on public data. METHODS: This was an observational, cross-sectional study. We included a total of 279 diagnosed children based on the data of children infected with SARS-CoV-2 reported by the Health Commission in each province, autonomous region, municipality, or special administrative region in China (outside of Hubei Province) from January 24, 2020 to February 16, 2020. RESULTS: The number of newborns (0 days ≤ age ≤28 days), infants (28 days < age ≤1 year), children (1 year < age ≤5 years), and children (5 years < age ≤18 years) accounted for 0.7%, 6.5%, 23.7%, and 69.2% of the total number of infected children, respectively. We found that from January 23, 2020, to January 31, 2020, infected children mainly came from Wuhan, China. After February 3, 2020, family clustering transmission became the main mode of transmission. CONCLUSIONS: Family clustering transmission is currently the main model of transmission in children. Considering the mild symptoms in infected children, the possibility that children may be a source of the transmission should not be ignored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".