Filling the knowledge gap: Scoping review regarding sampling methods, assays, and further requirements to assess airborne viruses
Bibliographic record
Abstract
Assessment of occupational exposure to viruses is crucial to identify virus reservoirs and sources of dissemination at an early stage and to help prevent spread between employees and to the general population. Measuring workers' exposure can facilitate assessment of the effectiveness of protective and mitigation measures in place. The aim of this scoping review is to give an overview of available methods and those already implemented for airborne virus' exposure assessment in different occupational and indoor environments. The results retrieved from the different studies may contribute to the setting of future standards and guidelines to ensure a reliable risk characterization in the occupational environments crucial for the implementation of effective control measures. The search aimed at selecting studies between January 1st 2010 and June 30th 2023 in the selected databases. Fifty papers on virus exposure assessment fitted the eligibility criteria and were selected for data extraction. Overall, this study identified gaps in knowledge regarding virus assessment and pinpointed the needs for further research. Several discrepancies were found (transport temperatures, elution steps, …), as well as a lack of publication of important data related to the exposure conditions (contextual information). With the available information, it is impossible to compare results between studies employing different methods, and even if the same methods are used, different conclusions/recommendations based on the expert judgment have been reported due to the lack of consensus in the contextual information retrieved and/or data interpretation. Future research on the field targeting sampling methods and in the laboratory regarding the assays to employ should be developed bearing in mind the different goals of the assessment.
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 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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".