• Study published in Nature Scientific Reports demonstrates embedded filters capture virus particles with limits of detection of ~10 copies per filter
  • Data consistent with findings that COVID is most infectious in early disease where breath aerosol viral load is highest
  • Sample collection by mask filter has strong potential applications in detection of bacterial and fungal respiratory infections

Cambridge, UK, 20 July 2021: Owlstone Medical (or the “Company”), the global leader in Breath Biopsy® for applications in early disease detection and precision medicine, today announced the publication of a peer-reviewed study in Nature Scientific Reports1. The paper investigates the performance of filters embedded in face masks for supporting the detection of SARS-CoV-2 as an alternative to nasopharyngeal swabs (NPS).

Diagnostic testing has been a cornerstone of the fight against COVID-19 from the start of the pandemic, however NPS, the gold standard for collection of samples, can be uncomfortable and difficult to administer. Therefore, a system that could passively collect a sample as part of daily routine would be of significant advantage as testing continues to be necessary in disease monitoring and control.

It is well understood that exhaled respiratory droplets or aerosols are the most common route of transmission of COVID-19, and that face masks are highly effective at limiting spread. This suggests that face masks retain viral particles and therefore could provide a convenient and non-invasive method of sampling for subsequent diagnostic testing.

To explore this, Owlstone Medical applied its breath-based diagnostic research expertise and Breath Biopsy technology to develop a system for the controlled generation of small aerosol particles to measure the limit of detection of viral capture on filters. Following this, hospitalized patients with confirmed COVID-19 were recruited to give samples of exhaled breath aerosol by breathing into a face mask for comparison with samples collected with NPS.

Study results demonstrated the ability of embedded filters to capture virus particles with very good limits of detection (~10 copies per filter). However, the study went on to show that viral load in COVID-positive patients had a significant impact on concordance between sample collection approaches, with the sensitivity of SARS-CoV-2 detection when using samples extracted from filters at less than 10% of NPS, with the positive cases correlating in those with the highest viral loads. These results are consistent with other studies where approximately 10% patients can account for as much 80% of infections2 and in later stages of disease, patients stay swab positive despite being non-infectious.

An additional consideration is that SARS-CoV-2 differs from many other respiratory viruses in that viral load in exhaled breath aerosols and infectiousness is highest before symptom onset and decreases thereafter3,4 As the majority of patients enrolled in the Company’s study had been first diagnosed and admitted to hospital several days before the collection of samples, this was proposed as a significant contributor to study findings.

These findings are in line with other recently published studies5,6, and suggest that a mask filter approach could potentially differentiate patients in the early stage of disease when they are most infectious. Further, there is strong evidence for mask-based sampling for the detection of bacteria or fungi such as Mycobacterium tuberculosis7, Aspergillus species8, or Pseudomonas aeruginosa9.

Billy Boyle, co-founder and CEO at Owlstone Medical said: “While our study demonstrated that the detection of SARS-CoV-2 on mask filters may not be suitable except for early disease, we are encouraged that our findings mirror that of the wider literature. More importantly, we now have a powerful capability to sample and analyze exhaled breath aerosol that can be more broadly applied. The potential to use mask filters to diagnose tuberculosis and other bacterial infections, and the ability to do so non-invasively, holds tremendous promise for community-based testing.”