Occurrence of SARS-CoV-2 infection among healthcare personnel: results from an early systematic review and meta-analysis.
Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 infection has become a global public health concern globally. Even though Healthcare Workers (HCWs) are supposedly at increased risk for SARS-CoV-2 infection, to date no pooled evidence has been collected. MATERIALS AND METHODS: We searched online electronic databases (PubMed, Embase, medRxiv.org for pre-prints) for all available contribution (up to May 20, 2019). Two Authors independently screened articles and extracted the data. The pooled prevalence of SARS-CoV-2 was analyzed using the random-effects model. The possible sources of heterogeneity were analyzed through subgroup analysis, and meta-regression. RESULTS: The overall pooled prevalence of SARS-CoV-2 was 3.5% (95%CI 1.8-6.6) for studies based on molecular assays, 5.5% (95%CI 2.1-14.1) for studies based on serological assays, and 6.5% (95%CI 2.5-15.6) for point-of-care capillary blood tests. Among subgroups, serological tests identified higher risk for SARS-CoV-2 seropositivity in physicians than in nurses (OR 1.436, 95%CI 1.026 to 2.008). Regression analysis indicated the possible presence of publication bias only for molecular tests (t -3.3526, p-value 0.002648). CONCLUSIONS: The overall pooled prevalence of SARS-CoV-2 was lower than previously expected, but available studies were affected by significant heterogeneity, and the molecular studies by significant publication bias. Therefore, further high-quality research in the field is warranted.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".