The Impact of Heating, Ventilation, and Air-Conditioning Design Features on the Transmission of Viruses, Including SARS-CoV-2: Overview of Reviews
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 or SARS-CoV-2 outbreak was declared a pandemic by the World Health Organization in March 2020. Almost 2 years later (early February 2022), the World Health Organization reported over 383 million cases of the disease caused by the virus, with over 5.6 million deaths worldwide. Debate regarding the routes of transmission was substantial early in the pandemic; however, airborne transmission emerged as an important consideration. Infectious airborne agents can spread within the built environment through heating, ventilation, and air-conditioning (HVAC) systems. Multiple features of HVAC systems can influence transmission (eg, ventilation, filtration, UV radiation, and humidity). Understanding how HVAC features influence airborne transmission is critical to mitigate the spread of infectious agents. OBJECTIVE: Given the airborne transmission of SARS-CoV-2, an overview of reviews was conducted to understand what is already known from the scientific literature about how virus transmission may be affected by HVAC design features in the built environment. METHODS: Ovid MEDLINE and Compendex were searched from inception to January 2021. Two reviewers independently screened the titles, abstracts, and full text of potentially relevant reviews, using a priori inclusion criteria: systematic reviews examining the effects of HVAC design features on virus transmission. Two reviewers independently assessed the methodological quality using AMSTAR2. RESULTS: Searching identified 361 citations, of which 45 (12.5%) were potentially relevant and 7 (2%) were included. Reviews were published between 2007 and 2021 and included 47 virus studies. Two earlier reviews (2007 and 2016) of 21 studies found sufficient evidence that mechanical ventilation (airflow patterns and ventilation rates) plays a role in airborne transmission; however, both found insufficient evidence to quantify the minimum mechanical ventilation requirements. One review (2017) of 9 studies examining humidity and indoor air quality found that influenza virus survival was lowest between 40% and 80% relative humidity; the authors noted that ventilation rates were a confounding variable. Two reviews (2021) examined mitigation strategies for coronavirus transmission, finding that transmission decreased with increasing temperature and relative humidity. One review (2020) identified 14 studies examining coronavirus transmission in air-conditioning systems, finding that HVAC systems played a role in virus spread during previous coronavirus outbreaks. One review (2020) examined virus transmission interventions in public ground transportation, finding ventilation and filtration to be effective. CONCLUSIONS: Seven reviews synthesizing 47 studies demonstrated a role for HVAC in mitigating airborne virus transmission. Ventilation, humidity, temperature, and filtration can play a role in the viability and transmission of viruses, including coronaviruses. Recommendations for minimum standards were not possible owing to few studies investigating a given HVAC parameter. This overview examining HVAC design features and their effects on the airborne transmission of viruses serves as a starting point for future systematic reviews and identifying priorities for primary research.
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 | 0,006 | 0,029 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,007 |
| Bibliométrie | 0,012 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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 ».