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Record W2279097798

Can we stop the spread of influenza in schools with face masks?

2009· article· en· W2279097798 on OpenAlexaff
Sara Y. Del Valle, Raymond Tellier, Gary S. Settles, Julian W. Tang

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2009
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAbsenteeismPandemicSocial distancePsychological interventionHygieneMedicinePreparednessIsolation (microbiology)Influenza pandemicEnvironmental healthFamily medicineCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)NursingPolitical sciencePsychologySocial psychologyLaw
DOInot available

Abstract

fetched live from OpenAlex

In the absence of a strain-specific vaccine and the potential resistance to antiviral medication, nonpharmaceutical interventions can be used to reduce the spread of an infectious disease such as influenza. The most common non-pharmaceutical interventions include school closures, travel restrictions, social distancing, enforced or volunteer home isolation and quarantine, improved hand hygiene, and the appropriate wearing of face masks. However, for some of these interventions, there are some unavoidable economic costs to both employees and employers, as well as possible additional detriment to society as a whole. For example, it has been shown that school-age children are most likely to be infected and act as sources of infection for others, due to their greater societal interaction and increased susceptibility. Therefore, preventing or at least reducing infections in children is a logical first-line of defense. For this reason, school closures have been widely investigated and recommended as part of pandemic influenza preparedness, and some studies support this conclusion. Yet, school closures would result in lost work days if at least one parent must be absent from work to care for children who would otherwise be at school. In addition, the delay in-academic progress may be detrimental due to mass school absenteeism. In particular, the pandemic influenza guidance by the U.S. Department of Health and Human Services recommends school closures for less than four weeks for Category 2 and 3 pandemics (i.e., similar to the milder 1957 and 1968 pandemics) and one to three months for Category 4 and 5 pandemics (i .e., similar to the 1918 pandemic ). Yet, given the above, it is clear that closing schools for up to three months is unlikely to be a practical mitigation strategy for many families and society. Thus modelers and policy makers need to weigh all factors before recommending such drastic measures, particularly if the agent under consideration typically has low mortality and causes a mild disease. Therefore, we contend that face masks are an effective, practical, non-pharmaceutical intervention that would reduce the spread of disease among school-children, while keeping schools open. Influenza spreads through person-to-person contact, via transmission by large droplets or aerosols (droplet nuclei) produced by breathing, talking, coughing or sneezing, as well as by direct (though most people touch very few others in their daily lives) or indirect (i.e., via fomites) contact. Face masks act as a physical barrier to reduce the amount of potentially infectious inhaled and exhaled particles, although they would not reliably protect the wearer against aerosols; a recent study also demonstrated that they can redirect and decelerate exhaled airflows (when worn by an infected individual) to prevent them from entering the breathing zones of others. Thus, if a whole classroom were to don face masks, disease transmission would be expected to be greatly diminished. Another recent study on face masks and hand hygiene show a 10-50% transmission reduction for influenza-like illnesses. Furthermore, face masks can act as an effective physical reminder and barrier to transmission by preventing the wearer from touching any potentially infectious secretions from their mucous membranes (i.e., from the nose and mouth), which is another mechanism for direct and indirect contact transmission for influenza. A recent systematic review has suggested that wearing masks can be highly effective in limiting the transmission of respiratory infections, such as influenza. Yet, admittedly, the effectiveness of this intervention strategy is highly dependent on compliance (i.e., the willingness to wear the mask in all appropriate situations), which in tum depends on comfort, convenience, fitness, and hygiene. Importantly, masks themselves must not become a source of infection (or reinfection); as such they should be replaced or sanitized daily (where possible) to maximize effectiveness. One solution could be for masks to be touted as fashion accessories, which may be particularly effective in influencing trend-conscious children. With support from the fashion industry and a child-targeted public health campaign, it may be possible to encourage such a trend and make the mask an acceptable fashion item, as well as an important means of infectious disease control.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0030.009
Open science0.0020.003
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0340.013

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.

Opus teacher head0.062
GPT teacher head0.323
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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