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Record W3209454683 · doi:10.1186/s12879-021-06802-4

COVID-19 transmission during swimming-related activities: a rapid systematic review

2021· review· en· W3209454683 on OpenAlexaff
Sally Yaacoub, Joanne Khabsa, Rayane El-Khoury, Amena El‐Harakeh, Tamara Lotfi, Zahra Saad, Zeina Itani, Assem M. Khamis, Ibrahim El Mikati, Carlos A. Cuello‐García, Francisca Verdugo‐Paiva, Gabriel Rada, Holger J. Schünemann, Nesrine Rizk, Elie A. Akl

Bibliographic record

VenueBMC Infectious Diseases · 2021
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcMaster UniversityImpactCochrane
FundersAmerican University of Beirut
KeywordsCoronavirus disease 2019 (COVID-19)Medical microbiology2019-20 coronavirus outbreakParasitologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Transmission (telecommunications)Tropical medicineMedicinePandemicVirologySystematic reviewDisease transmissionMEDLINEBiologyPathologyComputer scienceInfectious disease (medical specialty)DiseaseOutbreak

Abstract

fetched live from OpenAlex

BACKGROUND: There are uncertainties about mitigating strategies for swimming-related activities in the context of the COVID-19 pandemic. There is an opportunity to learn from the experience of previous re-openings to better plan the future one. Our objectives are to systematically review the evidence on (1) the association between engaging in swimming-related activities and COVID-19 transmission; and (2) the effects of strategies for preventing COVID-19 transmission during swimming-related activities. METHODS: We conducted a rapid systematic review. We searched in the L·OVE (Living OVerview of Evidence) platform for COVID-19. The searches covered the period from the inception date of each database until April 19, 2021. We included non-randomized studies for the review on association of COVID-19 transmission and swimming-related activities. We included guidance documents reporting on the strategies for prevention of COVID-19 transmission during swimming-related activities. We also included studies on the efficacy and safety of the strategies. Teams of two reviewers independently assessed article eligibility. For the guidance documents, a single reviewer assessed the eligibility and a second reviewer verified the judgement. Teams of two reviewers extracted data independently. We summarized the findings of included studies narratively. We synthesized information from guidance documents according to the identified topics and subtopics, and presented them in tabular and narrative formats. RESULTS: We identified three studies providing very low certainty evidence for the association between engaging in swimming-related activities and COVID-19 transmission. The analysis of 50 eligible guidance documents identified 11 topics: ensuring social distancing, ensuring personal hygiene, using personal protective equipment, eating and drinking, maintaining the pool, managing frequently touched surfaces, ventilation of indoor spaces, screening and management of sickness, delivering first aid, raising awareness, and vaccination. One study assessing the efficacy of strategies to prevent COVID-19 transmission did not find an association between compliance with precautionary restrictions and COVID-19 transmission. CONCLUSIONS: There are major gaps in the research evidence of relevance to swimming-related activities in the context of the COVID-19 pandemic. However, the synthesis of the identified strategies from guidance documents can inform public health management strategies for swimming-related activities, particularly in future re-opening plans.

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)0.055
metaresearch head score (Gemma)0.200
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.055
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.200
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0140.010
Bibliometrics0.0250.021
Science and technology studies0.0020.002
Scholarly communication0.0070.009
Open science0.0050.005
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.029
GPT teacher head0.337
Teacher spread0.308 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations13
Published2021
Admission routes1
Has abstractyes

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