Face mask use among individuals who are not medically diagnosed with COVID-19: A lack of evidence for and against and implications around early public health
Bibliographic record
Abstract
Aim: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, public health professionals from around the world have been making decisions on face mask use among individuals who are not medically diagnosed with COVID- 19 or "healthy individuals" to limit the spread of COVID-19. While some countries have strongly recommended face masks for "healthy individuals", other countries have recommended against it. Public health recommendations that have been provided to this population since the beginning of the outbreak have been controversial, contradicting, and inconsistent around the world. The purpose of this paper is to understand available evidence around the effectiveness or ineffectiveness of face mask use in limiting the spread of COVID-19 among individuals who have not yet been diagnosed with COVID-19 and most importantly, to understand the state of knowledge early public health recommendations are based on. Materials and Methods: A systematic review was conducted to identify studies that investigated the use of face masks to limit the spread of COVID-19 among "healthy individuals" in order to understand available evidence using the databases Cochrane Library, EMBASE, Google Scholar, PubMed, and Scopus. Two groups of keywords were combined: Those relating to COVID-19 and face masks. Results: No studies were found, demonstrating a lack of evidence for and against face mask use suggesting implications around early public health recommendations provided to "healthy individuals". Conclusion: Three and a half months into the COVID-19 outbreak (December 2019-2nd week of April 2020), there are no peer-reviewed scientific studies that have investigated the effectiveness or ineffectiveness of face mask use among "healthy individuals" to limit the spread of COVID-19. Yet, very strong public health recommendations have been provided on whether "healthy individuals" should or should not wear face masks to limit the spread of COVID-19 since the beginning of the outbreak. A lack of scientific evidence for and against face mask use heavily questions the basis of public health recommendations provided at a very early, yet a crucial stage of an outbreak. This finding and a further look at early public health recommendations conclude that there is a clear need for more concentrated research around face mask use among healthy individuals and public health recommendations that are evidence-based; precautionary in the absence of evidence; based on benefit-risk assessment; transparent; and globally aligned to provide the most successful guidelines during an infectious disease outbreak.
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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 | 0.011 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".