Environmental dissemination of respiratory viruses: dynamic interdependencies of respiratory droplets, aerosols, aerial particulates, environmental surfaces, and contribution of viral re-aerosolization
Bibliographic record
Abstract
During the recent pandemic of COVID-19 (SARS-CoV-2), influential public health agencies such as the World Health Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC) have favored the view that SARS CoV-2 spreads predominantly via droplets. Many experts in aerobiology have openly opposed that stance, forcing a vigorous debate on the topic. In this review, we discuss the various proposed modes of viral transmission, stressing the interdependencies between droplet, aerosol, and fomite spread. Relative humidity and temperature prevailing determine the rates at which respiratory aerosols and droplets emitted from an expiratory event (sneezing, coughing, etc .) evaporate to form smaller droplets or aerosols, or experience hygroscopic growth. Gravitational settling of droplets may result in contamination of environmental surfaces (fomites). Depending upon human, animal and mechanical activities in the occupied space indoors, viruses deposited on environmental surfaces may be re-aerosolized (re-suspended) to contribute to aerosols, and can be conveyed on aerial particulate matter such as dust and allergens. The transmission of respiratory viruses may then best be viewed as resulting from dynamic virus spread from infected individuals to susceptible individuals by various physical states of active respiratory emissions, instead of the current paradigm that emphasizes separate dissemination by respiratory droplets, aerosols or by contaminated fomites. To achieve the optimum outcome in terms of risk mitigation and infection prevention and control (IPAC) during seasonal infection peaks, outbreaks, and pandemics, this holistic view emphasizes the importance of dealing with all interdependent transmission modalities, rather than focusing on one modality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".