Re: It Is Time to Address Airborne Transmission of COVID-19
Notice bibliographique
Résumé
To the Editor—We are concerned that the commentary by Morowska and Milton [1] has caused significant confusion. We agree that there is a gradient from large droplets to aerosols. We also agree that under experimental conditions and possibly in poorly ventilated, indoor, crowded environments there is potential for the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by aerosols. Furthermore, we agree that the availability of adequate ventilation indoors and the use of outdoor space have validity in preventing transmission. However, we argue that the epidemiologic data and clinical experience in managing the pandemic continue to support that the main mode of SARS-CoV-2 transmission is short range through droplets and close contact [2]. The concerns raised by the authors are not borne out in clinical experience. Long-range transmission beyond 2 meters in the more than 10 000 patients with coronavirus disease 2019 (COVID-19) hospitalized nationally in Canada and elsewhere seems rare at best. Current policies in many international jurisdictions recommend droplet/contact precautions for routine care of patients with suspected or confirmed COVID-19 and the addition of airborne precautions only for aerosol-generating medical procedures (AGMPs) [3]. Epidemiologic studies support this approach and even suggest that AGMP transmission risk may be overestimated [4]. In the case of the healthcare environment, we did not find any convincing evidence in their review to change occupational health and infection control practices. In contrast, real-world experiences have been published where, despite significant aerosol generation, rates of transmissions have been minimal. The first community-acquired COVID-19 case in the United States underwent multiple high-risk prolonged AGMPs [5]. Despite 121 exposures without N95 respirators, only 3 (2.5%) healthcare workers acquired SARS-COV-2, 2 of whom did not wear any respiratory protection at all and the third wore a surgical mask intermittently. In Singapore, 41 healthcare workers were exposed to multiple prolonged AGMPs in a COVID-19 patient, only 6 wore N95 respirators [6]. On serial testing, no staff acquired COVID-19. These observational case reports substantiate the Canadian experience in which COVID-19 patients are routinely managed with droplet/contact precautions; there has been no increased risk of infections in healthcare workers when compared with community populations [7]. Published case series of nonhealthcare settings confirm the findings of droplet/contact transmission, including a flight where only a single adjacent passenger was secondarily infected [8] and a cluster of infections at a call center related to close contact within a building [9], as well as multiple household contact studies with secondary attack rates of less than 20% [10]. Evidence-based policy around infection prevention should be informed by research from the physical sciences, biology, and epidemiology, with consideration of real-life aspects. We commend the authors for highlighting relevant experimental evidence. However, without reconciling with the clinical real-world experience of COVID-19, the authors draw premature conclusions about the importance of airborne transmission. This has resulted in confusion and fear in the general public, mistrust in healthcare workers, and a risk of a deepening divide between experimental scientists and healthcare epidemiologists. Supplementary materials are available at Clinical Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author. Potential conflicts of interest. S. H. reports a research study grant from Finch Therapeutics outside the submitted work. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,003 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,108 | 0,057 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,039 | 0,019 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».