Nonpharmaceutical interventions to prevent viral respiratory infection in community settings: an umbrella review
Bibliographic record
Abstract
Background: Respiratory viruses pose an important public health threat to most communities. Nonpharmaceutical interventions (NPIs) such as masks, hand hygiene or physical distancing, among others, are believed to play an important role in reducing transmission of respiratory viruses. In this umbrella review, we summarise the evidence of the effectiveness of NPIs for the prevention of respiratory virus transmission in the community setting. Observations: A systematic search of PubMed, Embase, Medline and Cochrane reviews resulted in a total of 24 studies consisting of 11 systematic reviews and meta-analyses, 12 systematic reviews without meta-analyses and one standalone meta-analysis. The current evidence from these data suggests that hand hygiene is protective against respiratory viral infection. The use of hand hygiene and facemasks, facemasks alone and physical distancing were interventions with inconsistent evidence. Interventions such as school closures, oral hygiene or nasal saline rinses were shown to be effective in reducing the risk of influenza; however, the evidence is sparse and mostly of low and critically low quality. Conclusions: Studies on the effectiveness of NPIs for the prevention of respiratory viral transmission in the community vary in study design, quality and reported effectiveness. Evidence for the use of hand hygiene or facemasks is the strongest; therefore, the most reasonable suggestion is to use hand hygiene and facemasks in the community setting.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".