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Ventilation and detection of airborne SARS-CoV-2: elucidating high-risk spaces in naturally ventilated healthcare settings (preprint)
medrxiv; 2021.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2021.06.30.21258984
ABSTRACT

Background:

In healthcare settings in low- and middle-income countries, which frequently rely upon natural ventilation, the risk of aerosol transmission of SARS-CoV-2 remains poorly understood. We aimed to evaluate the risk of exposure to SARS-CoV-2 in naturally-ventilated hospital settings by measuring parameters of ventilation and comparing these findings with results of bioaerosol sampling.

Methods:

We measured outdoor and room CO2 to estimate absolute ventilation (liters per second [L/s]) from 9 hospitals in Bangladesh during October 2020 - February 2021. We estimated infectious risk across different spaces using a modified Wells-Riley equation. We collected air samples from these same spaces at 12.5 L/min over 30 minutes and performed RT-qPCR to detect SARS-CoV-2 N-gene. We used multivariable linear regression and calculated elasticity to identify characteristics associated with ventilation.

Results:

Based on ventilation of 86 patient care areas and COVID-19 case numbers, we found that over a 40-hour exposure period, outpatient departments posed the highest median risk for infection (5.4%), followed by COVID intensive care units (1.8%). We detected SARS-CoV-2 RNA in 18.6% (16/86) of air samples. Ceiling height and total open area of doors and windows were found to have the greatest impact on ventilation.

Conclusion:

Our findings provide evidence that naturally-ventilated healthcare settings may pose a high risk for exposure to SARS-CoV-2, particularly among non-COVID designated spaces, but improving parameters of ventilation can mitigate this risk.
Subject(s)

Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2021 Document Type: Preprint