Exhaled SARS-CoV-2 quantified by face-mask sampling in hospitalised patients with COVID-19

Abstract

Background: Human to human transmission of SARS-CoV-2 is driven by the respiratory route but little is known about the pattern and quantity of virus output from exhaled breath. We have previously shown that face-mask sampling (FMS) can detect exhaled tubercle bacilli and have adapted its use to quantify exhaled SARS-CoV-2 RNA in patients admitted to hospital with Coronavirus Disease-2019 (COVID-19).

Methods: Between May and December 2020, we took two concomitant FMS and nasopharyngeal samples (NPS) over two days, starting within 24 h of a routine virus positive NPS in patients hospitalised with COVID-19, at University Hospitals of Leicester NHS Trust, UK. Participants were asked to wear a modified duckbilled facemask for 30 min, followed by a nasopharyngeal swab. Demographic, clinical, and radiological data, as well as International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) mortality and deterioration scores were obtained. Exposed masks were processed by removal, dissolution and analysis of sampling matrix strips fixed within the mask by RT-qPCR. Viral genome copy numbers were determined and results classified as Negative; Low: ≤999 copies; Medium: 1000-99,999 copies and High ≥ 100,000 copies per strip for FMS or per 100 µl for NPS.

Results: 102 FMS and NPS were collected from 66 routinely positive patients; median age: 61 (IQR 49 - 77), of which FMS was positive in 38% of individuals and concomitant NPS was positive in 50%. Positive FMS viral loads varied over five orders of magnitude (<10-3.3 x 10⁶ genome copies/strip); 21 (32%) patients were asymptomatic at the time of sampling. High FMS viral load was associated with respiratory symptoms at time of sampling and shorter interval between sampling and symptom onset (FMS High: median (IQR) 2 days (2-3) vs FMS Negative: 7 days (7-10), p = 0.002). On multivariable linear regression analysis, higher FMS viral loads were associated with higher ISARIC mortality (Medium FMS vs Negative FMS gave an adjusted coefficient of 15.7, 95% CI 3.7-27.7, p = 0.01) and deterioration scores (High FMS vs Negative FMS gave an adjusted coefficient of 37.6, 95% CI 14.0 to 61.3, p = 0.002), while NPS viral loads showed no significant association.

Conclusion: We demonstrate a simple and effective method for detecting and quantifying exhaled SARS-CoV-2 in hospitalised patients with COVID-19. Higher FMS viral loads were more likely to be associated with developing severe disease compared to NPS viral loads. Similar to NPS, FMS viral load was highest in early disease and in those with active respiratory symptoms, highlighting the potential role of FMS in understanding infectivity.

Graphical abstract

Fig. 1

Photograph of duckbilled-mask used, and sampling strips that are fixed within the inside of the mask, that can be removed for analysis.

Fig. 2

Relationship between FMS and NPS viral loads. Abbreviations used: FMS – face-mask sampling; NPS – nasopharyngeal sampling. Coloured symbols represent samples with a disproportionately high FMS viral load than predicted by regression line. Blue symbols denote day 1 and 2 samples from an individual judged asymptomatic for COVID-19.

Fig. 3

FMS (3a) and NPS (3b) viral copy numbers in relation to number of days symptomatic prior to sampling. Abbreviations used: FMS – face-mask sampling; NPS – nasopharyngeal sampling. Alternatively coloured symbols denote the three symptomatic high FMS samples shown in Fig. 2.