Air change rate and SARS-CoV-2 exposure in hospitals and residences: A meta-analysis

Abstract

As COVID-19 swept across the globe, increased ventilation and implementation of air cleaning were emphasized by the US CDC and WHO as important strategies to reduce the risk of inhalation exposure to the virus. To assess whether higher ventilation and air cleaning rates lead to lower exposure risk to SARS-CoV-2, 1274 manuscripts published between April 2020 and September 2022 were screened using key words “airborne SARS-CoV-2 or “SARS-CoV-2 aerosol.” Ninety-three studies involved air sampling at locations with known sources (hospitals and residences) were selected and associated data were compiled. Two metrics were used to assess exposure risk: SARS-CoV-2 concentration and SARS-CoV-2 detection rate in air samples. Locations were categorized by type (hospital or residence) and proximity to the location housing the isolated/quarantined patient (primary or secondary). The results showed that hospital wards had lower airborne virus concentrations than residential isolation rooms. A negative correlation was found between airborne virus concentrations in primary-occupancy areas and air changes per hour (ACH). In hospital settings, sample positivity rates were significantly reduced in secondary-occupancy areas compared to primary-occupancy areas, but they were similar across sampling locations in residential settings. ACH and sample positivity rates were negatively correlated, though the effect was diminished when ACH values exceeded 8. While limitations associated with diverse sampling protocols exist, data considered by this meta-analysis support the notion that higher ACH may reduce exposure risks to the virus in ambient air.

Copyright © 2024 American Association for Aerosol Research

Graphical Abstract

EDITOR:

• Vishal Verma

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by National Institutes of Health (Grant No. R01AI158868, R01AI158868S1, R21OH012114, and R43AI157123). Tuition for William B. Vass was paid through the U.S. Army Medical Service Corps Long-Term Health Education and Training fellowship, and for Sripriya Nannu Shankar through NIH-NCATS under UF and FSU CTSI awards (TL1TR001428 & UL1TR001427) and Herbert Wertheim College of Engineering, UF. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Institutes of Health.